Changelog
Source:NEWS.md
emmeans 1.10.5-090xxx
- Added new
add_submodels()
function that allows for comparison od estimates from different submodels (when supported) - Additional notes for
eff_size()
. Also, an questionable example was deleted. It is so easy to misuse this function, and I don’t even buy into the idea of standardized effect sizes except in the simplest of cases. So I am considering deprecatingeff_size()
and letting some other package be to blame for unsuitable or misleading results.
emmeans 1.10.5
CRAN release: 2024-10-14
- Fix for long-standing
weights
bug inlme()
(#356) - Fix for inconsistent contrasts in case of missing levels (#508, #509)
- Fix for using nuisance variables with proportional weights (#510)
- New function
with_emm_options()
to run code with options temporarily set - Tweak to optimal-digits output that shows
SE
to 3 significant digits
emmeans 1.10.4
CRAN release: 2024-08-21
- Refinements in tracking static offsets
- Made d.f. consistent for
geeglm
andglmgee
(#496) - Fixed suggestion for installing from GitHub (#497)
- Change that allows factors to have
NA
levels (#500). This was previously not allowed, and we added an"allow.na.levs"
option (defaults toTRUE
) just in case we broke anything that used to work. - Better default contrasts in
qdrg()
(#501) - Bug fix for nuisance factors when we have a multivariate response (#503)
- Improved auto-detection of response transformation (#504)
- Bug fix for detecting cases where we can’t use
nuisance
(#503) - New
mvregrid()
function for multivariate response transformations such as a compositional response.
emmeans 1.10.3
CRAN release: 2024-07-01
- Updated
mice::mira
support to use Barnard-Rubin adjusted d.f. (#494) - Fix to MuMIn support so a response transformation is auto-detected
- Bug fix in
gls
support code (#495) - I am trying to be clearer that some model-support modes cause implied re-gridding, making the link function no longer operable. A new subsection discussing this was added to the “Transformations” vignette, and I also added indications of this to the “models” vignette.
- Don’t think too hard about which recent updates (since 1.8.9) are more major than others. I’ll try to be more rational about this going forward.
emmeans 1.10.2
CRAN release: 2024-05-20
This update is focused mostly on trying to clear up confusion with some users on the distinction between emmGrid
objects and their summaries, since they display identically; and on encouraging users not to bypass important annotations.
- Added a startup message and
help(untidy)
- Added
rbind
method forsummary_emm
objects (#480). Note thatsummary_emm
objects already have estimates, P-values, etc. computed, sorbind
ing them preserves those results. On the other hand,rbind
ingemmGrid
oremm_list
objects produce newemmGrid
objects which have not yet been summarized and anyadjust
methods are applied to the whole result. - Created pkgdown site
emmeans 1.10.1
CRAN release: 2024-04-06
- With
gls
orlme
models,mode = "satterthwaite"
andmode = "appx-satterthwaite"
failed when model was fitted with no explicitdata
argument (#465) - We decided to export the
.emmc
functions, just to make it easier to see and use them - Added a new contrast function
wtcon.emmc(levs, wts, cmtype, ...)
which generates contrasts viamultcomp::contrMat(wts, type = cmtype, ...)
-
contrast()
gains a new argumentwts
which can be passed to some.emmc
functions includingeff.emmc
,del.eff.emmc
, andwtcon.emmc
. Ifwts
is left missing, we pass equal weights of. If we specify
wts = NA, we retrieve weights from the object (potentially different in each
bygroup). Otherwise, the same fixed
wts` are used in each group. - Added a
weights()
method foremmGrid
objects - Modification to
pwpp()
to play along ifcontrast()
changes theby
variable viaoptions
(#472) - After some wiggling around, we now allow
strata()
factors to be included in the reference grid for survival models. It is up to the user to decide what is sensible. (#429, #473)
emmeans 1.10.0
CRAN release: 2024-01-23
- Restored
tau
argument (now optional) for rq models (#458) - Fixed issue where a multivariate factor having numeric levels may mismatch a level in
at
even when apparently valid (#458) - Added
cross.adjust
to legal arguments that can be passed viamisc
slot - Robustified code for
cross.adjust
- Fixed masking of
vcov.
inglmgee
support (#460) - Fixed an error in
xtable()
method forsummary_emm
objects - Added
inner
argument tomake.tran()
to allow for compound transform; e.g.,make.tran("inverse", inner = "sqrt")
is reciprocal sqrt (#462)
emmeans 1.9.0
CRAN release: 2023-12-18
- Warning message about prior weights was sometimes unnecessary. We now suppress it when all the prior weights are equal.
- Fix to
MuMIn
support withsubset
argument (#455) - Repair to coding error for nested models (#457)
- Added
glmtoolbox::glmgee
support (#454) -
qdrg()
modified such that we often don’t need to specifydata
whenobject
is specified. - Support for for
rq
,rqs
now incorporates alltau
values in the model as a pseudofactor (#458). Thetau
argument itself is deprecated and ignored if specified.
emmeans 1.8.9
CRAN release: 2023-10-17
- Added functions
make.meanint()
andmake.symmint()
that return functions that compute symmetric intervals. The oldmeanint()
andsymmint()
functions that return symmetric intervals of width2
are retained for back-compatibility - Small repairs to
multinom
support so it works with a model where the response is a matrix of counts (#439) - Enhancements/fixes for
MuMIn
support (#442) -
qdrg()
has replaced itsordinal.dim
argument withordinal
, a list with elementsdim
andmode
– which now fully supports all the modes available for ordinal models (#444). (ordinal.dim
still works for backward compatibility.) - Fix to bookkeeping bug in
emtrends
(#448) - Fix to
averaging
support with certain predictor function calls (#449)
emmeans 1.8.8
CRAN release: 2023-08-17
- Bug correction in
contrast
whentran
is alist
(#428) - Bug correction to suppress a nuisance warning when the number of prior weights is 0 or 1 (which indeed doesn’t match the number of rows of data, but also isn’t really an issue) (Commit d921152 for easystats)
- Bug correction for
strata()
terms in survival models (#429) - Added a risk-ratio and a probit example to the Transformations vignette.
- Multivariate levels were mishandled when specified out of order in
at
(#430) - Fix to flow error in
qdrg()
where we didn’t always getV
right - Change to adjustment methods when there are non-estimable cases. Now we always adapt the family size to include only the estimable ones. This may change some adjusted P values or confidence limits obtained in past versions, when the model is rank-deficient.
-
vcov.emmGrid()
now only returns elements whereobject@misc$display == TRUE
. We also label the dimensions and provide asep
argument for creating labels.
emmeans 1.8.7
CRAN release: 2023-06-23
-
Correction to a bug introduced in version 1.8.4, where we tried to provide for an
offset
argument in the same way as anoffset()
term in the model formula. Unfortunately, that change also caused wrong estimates to be computed when the offset involves a nonlinear function such aslog()
, and made for whopping inconsistencies in the narrative about offsets in the"sophisticated"
vignette; I apologize for these embarrassing errors.We now provide for both kinds of offset specifications, but in different ways as explained in a new section in the
"xplanations"
vignette. The “subtle difference” mentioned in the NEWS for 1.8.4 no longer applies. Change in
qdrg()
. Ifobject
is specified, default fordf
isdf.residual(object)
rather thanobject$df.residual
, sincedf.residual()
is a standard method.as.mcmc()
now usesget_emm_option("sep")
in labeling factor combinations (#425).
emmeans 1.8.6
CRAN release: 2023-05-11
- Major fix to
emm_basis.averaging
to take care of quirks in these models (#402, #409) - Added
decreasing
argument tocld.emmGrid()
for compatibility withmultcomp::cld.glht()
and others. - Fix to bug in
emtrends()
whendata
is specified (semTools issue 119) … and related tune-up toref_grid()
to avoid issues with repeat calls (#413) - Tweak to
emm_list
methods to make them more user-friendly (#417) - We added a
pwts
argument torecover_data.call()
, needed because prior weights did not always come through. This provides a reliable way of passing prior weights in arecover_data()
method
emmeans 1.8.5
CRAN release: 2023-03-08
- passing scale info to
emmip_ggplot()
(#397) - Changes to
as.data.frame
behavior. It has been made more forceful in preserving annotations (i.e.,summary_emm
behavior) so that users don’t blind themselves to potentially important information. Also, some users seem to force display of the data frame in order to see more digits; so we now are taking a compromise approach: showing more digits but still as asummary_emm
object with annotations also displayed. - Added
Chisq
value to results oftest(..., joint = TRUE)
andjoint_tests()
whendf2
is infinite (per request in #400) - The
basics
vignette has undergone a major revision that I hope helps more in getting users oriented. It starts by discussing the fact that EMMs’ underpinnings are more in experiments than observational data, and emphasizes more the process of first getting a good model. - The
confidence-intervals
vignette has been updated to reflect the same example withpigs
as is used inbasics
- Following Issue #403 on GitHub, we are taking a much stricter approach with anything involving the
sigma
value in the@misc
slot. For any models that are not in the"gaussian"
family,sigma
is initialized toNA
and this has some implications:-
Bias adjustment: Bias adjustment is disabled by default for all non-Gaussian family models, and a warning is issued. You can enable bias adjustment by providing a valid
sigma
value; however, for generalized linear models the value ofsigma(model)
is often inappropriate for bias adjustment, and in fact anyway. you should not do that*, and for mixed models, you should calculatesigma
based on the random effects. See the vignette on transformations. -
Prediction intervals: With non-Gaussian models,
predict(..., interval = "prediction")
will refuse to work, with no option to override. Same with specifyingPIs = TRUE
inplot()
oremmip()
. The calculations done for prediction intervals are only valid for Gaussian models. You may do predictions for non-Gaussian models via simulating a posterior predictive distribution with Bayesian approach; see an illustration in the “sophisticated” vignette. - The above changes will help reduce the incidence of users using the package incorrectly with GLMs, GLMMs, and GEEs. But there’s still the issue that Gaussian mixed models will often have a wrong default
sigma
value associated with them, resulting in incorrect PIs and incorrect bias adjustments. I have not figured out how I might help prevent that, but it probably will involve making tedious modifications to these models’emm_basis
methods. Maybe some future improvements to be made.
-
Bias adjustment: Bias adjustment is disabled by default for all non-Gaussian family models, and a warning is issued. You can enable bias adjustment by providing a valid
- Bug fix for matching terms in
averaging
objects (#402) - Bug fix for
mira
objects whendata
is required (#406)
emmeans 1.8.4
Fix to
scale()
response transformation when eithercenter
orscale
isFALSE
. I also added support forcenter()
andstandardize()
from the datawizard package as response transformations, though these are mapped toscale()
.Citation correction (#391)
Removed a message about contrasting transformed objects that even confuses me! (I added a topic in the FAQs vignette instead)
Added new exported function
inverse
available as a response transformationI have quietly deprecated the previous
I_bet()
function, because it produced a message that was confusing to inexperienced users. Instead, we have tweaked some functions/methods so they seem to work the same way with anemm_list
object (using its first element) as anemmGrid
object.We have removed the functions
convert_workspace()
andconvert_scripts()
that were intended to clean up existing code and objects for the ancient version of lsmeans. We also completely removed several old functions from the codebase. Previously, we just ignored them.More reliable dispatching of
recover_data()
andemm_basis()
methods (#392)New
permute_levels()
function to change the order of levels of a factor (#393)-
This may alter results of existing code for models involving offsets: A user discovered an issue whereby offsets specified in an
offset()
model term are accounted for, but those specified in anoffset = ...
argument are ignored. We have revised therecover_data()
andref_grid()
code so that offsets specified either way (or even both) are treated the same way (which is to include them in predictions unless overridden by anoffset
argument inemmeans()
orref_grid()
).This change creates a subtle difference in cases where you want offsets to depend on other predictors: In a model with formula
y ~ trt + offset(off)
, if you used to specifycov.reduce = off ~ trt
, now you needcov.reduce = .offset. ~ trt
. The latter will work the same with the modely ~ trt, offset = off
. Recoded some portions of the support functions for
zeroinfl
andhurdle
objects. We now use numerical differentiation to do the delta method, and this comes out a lot cleaner.Per the improved count-model support, we are now exporting and have documented two new functions
hurdle.support()
andzi.support()
that may be useful in providing comparable support in other packages that offer zero-inflated models.Efficiency improvements: Several places in the code where we multiply a matrix by a diagonal matrix, we replace this by equivalent code using the
sweep()
function.-
Over time, too many users have latched on to the idea that
emmeans(model, pairwise ~ treatment(s))
as the recipe for usingemmeans()
. It works okay when you have just one factor, but when you have three factors, say,pairwise ~ fac1*fac2*fac3
gives you every possible comparison among cell means; often, this creates an intractable amount of output (e.g., 378 comparisons in a 3x3x3 case) – most of which are diagonal comparisons.So now, if a user is in interactive mode, specifies contrasts in a direct
emmeans()
call (i.e.,sys.parent() == 0
), there is more than one primary factor (not includingby
factors), and there are more than 21 contrasts as a result (e.g. more than 7 levels compared pairwise), we issue an advisory warning message: “You may have generated more contrasts than you really wanted…”. Because of the restrictions on when this warning is issued, it should not affect reverse-dependent package checks at all.
emmeans 1.8.3
CRAN release: 2022-12-06
- Fix to logic error in
regrid()
(#287, revisited) - Fix to
nbasis
calculation in ordinal models (#387) - Bias-adjustment example added when we have random slopes
- New
addl.vars
argument allows including variables (say, for random slopes) in the reference grid. - Removed dependence on xtable package. The
xtable
methods are now dynamically registered. This reduces the number of package dependencies from 8 to 7 (as of this version). - Added alt text to all pictures in vignettes (#389). This makes the materials more accessible per guidelines from the A11Y project.
- Added
"atanh"
to the options inmake.tran()
and to the “named” response transformations that are auto-detected -
make.tran()
replacesparam
argument withalpha
andbeta
(param
is still supported for backward compatibility) and documentation has been revised in hopes of making everything clearer
emmeans 1.8.2
CRAN release: 2022-10-27
- Extended
cld()
so it can show findings rather than non-findings, in two different ways: Usingdelta
, groupings are based on actual tests of equivalence with thresholddelta
; or settingsignif.sets = TRUE
, means that have the same letter are significantly different. We also added a vignette on “Re-engineering CLDs”. - Bug fix for subtle error in
emtrends()
(#133) - Improved customization of
emmip()
so that we can specifycolor
,linetype
, andsymbol
are all associated with groupings; and addition of an example to produce a black-and-white plot. Note: While the default appearance of plots is unchanged, plots from your existing code may be altered if you have usedlinearg
,dotarg
, etc. - Allow
vcov.
to be coercible to a matrix, or a function that yields a result coercible to a matrix (#383) - Robustness improvement for
"appx-satterthwaite"
method (#384) - Added
counterfactuals
argument toref_grid()
, setting up a reference grid consisting of the stated factors and a constructed factor,.obs.no.
. We then (by default) average this grid over the covariate distribution. This facilitates G-computation under the exchangeability assumption for counterfactuals.
emmeans 1.8.1
- Fixed new bug in
summary()
introduced in #359 and reported in #364 - Fixed
as.data.frame.emm_list()
so it preserves annotations like inas.data.frame.emmGrid()
- Fix to
mgcv::gam
support to accommodate fancier smoothers and more accurately detect random terms (#365, #366, #369) - Fix in call to
summary()
from inside a function (#367) - Added a
delta
argument tohpd.summary()
, thus allowing a way to assess equivalence with Bayesian estimates (#370) - Bug fix for
stanreg
estimability code whensubset
was used in model. -
emmip()
andplot.emmGrid()
now do appropriate things ifpoint.est
orfrequentist
appear among the...
arguments, when we have Bayesian models (note also,frequentist
was removed from the visible arguments forplot.emmGrid
). - With Bayesian models,
emmip()
plotted intervals regardless ofCIs
; this has been corrected - Added
head()
andtail()
methods foremmGrid
objects - In
[.summary_emm()
, we changed the default toas.df = FALSE
so that annotations are still visible by default. This also preserves annotations inhead()
andtail()
for summaries - New
emm_example()
function used to tidy-up certain help-file examples when they are conditional on an external package - Continued efforts to prevent users from hiding annotations they need to see. The functions/methods
summary()
,confint()
,test()
, andas.data.frame()
all produce data frames with annotations intact and visible. Additional wrapping indata.frame()
,as.data.frame()
, etc. is completely unnecessary, and if you send questions or bug reports with such code, I will regard it as willful ignorance and will refuse to respond. See also the news for version 1.8.0.
emmeans 1.8.0
CRAN release: 2022-08-05
- Fixed minor bug in
lme
support (#356) - Added support for
svyolr
objects from the survey package (#350) - Improvements to
mgcv::gam
support. Previously, random smoothers were included. Thanks for Maarten Jung for observing this and helping to identify them. - Improvements to
test(..., joint = TRUE)
andjoint_tests()
…- Sometimes did incorrect computations with rank deficient models
-
"est.fcns"
attribute is actually estimable - Results for
(confounded)
entry injoint_tests()
is now much better formulated and more robust. - Added section related to this in
xplanations
vignette - Version dependency for
estimability (>= 1.4.1)
due to a bug in version 1.4
- In
joint_tests()
, we changed the default fromcov.reduce = range
tocov.reduce = meanint
, wheremeanint(x)
returnsmean(x) + c(-1, 1)
. This centers the covariate values around their means, rather than their midranges, and is more in line with the default ofref_grid(..., cov.reduce = mean)
. However, this change in default will change the results ofjoint_tests()
from past experiences with models having covariates that interact with factors or other covariates. We also added a section on covariates to the help forjoint_tests()
, and added another functionsymmint()
for use incov.reduce
. -
print.summary_emm()
now putsby
groups in correct order rather than in order of appearance. - The
as.data.frame
method has a new argumentdestroy.annotations
, which defaults toFALSE
– in which case it returns asummary_emm
object (which inherits fromdata.frame
). I see that many users routinely wrap their results inas.data.frame
because they want to access displayed results in later steps. But in doing so they have missed potentially useful annotations. Users who have usedas.data.frame
to see results with lots of digits should instead useemm_options(opt.digits = FALSE)
. - New R version dependency
>= 4.1.0
, allowing freedom to use the forward pipe operator|>
and other features. -
Housecleaning: We removed completely the
trend
argument inemmeans()
, which has long since been deprecated. We removed wrappers that implementpmmeans()
,pmtrends()
, etc. – which I believe nobody ever used.
emmeans 1.7.5
CRAN release: 2022-06-22
- Modified the defaults for several methods for class
emm_list
, and added more complete documentation. We also added hiddenemm_list
support to several functions likeadd_grouping()
,emmip()
, andemmeans()
itself. These changes, we hope, help in situations where users create objects likeemm <- emmeans(model, pairwise ~ treatment)
but are not experienced or attuned to the distinction betweenemmGrid
andemm_list
objects. The mechanism for this is to provide a default of for which element of theemm_list
to use. A message is shown that specifies which element was selected and encourages the user to specify it explicitly in the future via either[[ ]]
or awhich
argument; for example,plot(emm[[1]])
orplot(emm, which = 1)
. - The object returned by
joint_tests()
andtest(..., joint = TRUE)
now has an"est.fcns"
attribute, which is a list of the linear functions associated with the joint test(s). -
joint_tests()
results now possibly include a(confounded)
entry for effects not purely explained by a model term.f - New
cross.adjust
argument insummary.emmGrid()
allows for additional P-value adjustment acrossby
groups. - Apparently,
glm.nb
support no longer requiresdata
(#355) so the documentation was updated.
emmeans 1.7.4
- Added an argument
enhance.levels
tocontrast()
that allows better labeling of the levels being contrasted. For example, now (by default) if a factortreat
has numeric levels, then comparisons will have levels liketreat1 - treat2
rather than1 - 2
. We can request similar behavior with non-numeric levels, but only if we specify which factors. - Two new functions
comb_facs()
andsplit_fac()
for manipulating the factors in anemmGrid
. - Added an argument
wts
toeff.emmc
anddel.eff.emmc
, which allows for weighted versions of effect-style contrasts (#346) - Made
qdrg()
more robust in accommodating various manifestations of rank-deficient models. -
qdrg()
now always usesdf
if provided. Previously forceddf = Inf
when a link function was provided. - Fix to
df.error
calculation withgls
(#347)
emmeans 1.7.3
CRAN release: 2022-03-27
-
argument change
ref_grid(..., transform = ...)
now should beref_grid(..., regrid = ...)
to avoid confusingtransform
with thetran
option (which kind of does the opposite). If we matchtransform
and don’t matchtran
, it will still work, but a message is displayed with advice to useregrid
instead. - Repairs to
averaging
support (#324). Previous versions were potentially dead wrong except for models created bylm()
(and maybe some of those were bad too) - Added a
which
argument toemm()
to select which list elements to pass tomultcomp::glht()
- Support for rank-deficient
gls
models (note that nlme allows such models withgls
, but notlme
) - Bug in
lqm
/lqmm
support (#340) - Other minor corrections (e.g. #334)
emmeans 1.7.2
CRAN release: 2022-01-04
- Improvements to
averaging
support (#319) - Fixed bug in comparison arrows when
by = NULL
(#321) (this bug was a subtle byproduct of the name-checking in #305) Note this fixes visible errors in the vignettes for ver 1.7.1-1 - Patch for
gamlss
support (#323) - Added
withAutoprint()
to documentation examples withrequire()
clauses, so we see interactive-style results - Correction to a logic error in adjustment corrections in
summary.emmGrid
(#31) - Revised
summary.emmGrid()
so that if we have both a response transformation and a link function, then both transformations are followed through withtype = "response"
. Previously, I took the lazy way out and usedsummary(regrid(object, transform = "unlink"), type = "response")
(see #325) - Fix to
force_regular()
which caused an unintended warning (#326) - Fixes to issues in
emtrends()
(#327)
emmeans 1.7.1
- Support from multinomial models in mgcv::gam (#303) thanks to Hannes Riebl
- Bug fix for spaces in
by
variable names (#305). Related to this are:-
plot.emmGrid()
now forces all names to be syntactically valid - In
as.data.frame.emmGrid()
, we changed theoptional
argument tocheck.names
(defaulting toTRUE
), and it actually has an effect. So by default, the result will have syntactically valid names; this is a change, but only becauseoptional
did not work right (because it is an argument for `as.data.frame.list()).
-
- Fix for missing column names in
linfct
fromemmeans()
(#308) - Added
gnls
support (#313, #314, thanks to Fernando Miguez) - Modified
glm
support so thatdf.residual
is used when the family is gaussian or gamma. Thus, e.g., we matchlm
results when the model is fitted with a Gaussian family. Previously we ignored the d.f. for allglm
objects. - New vignette example with percentage differences
- More graceful handling of comparisons when there is only one mean; and a related FAQ
emmeans 1.7.0
CRAN release: 2021-09-29
Notable changes
- New
rg.limit
option (and argument forref_grid()
) to limit the number of rows in the reference grid (#282, #292). This change could affect existing code that used to work – but only in fairly extreme situations. Some users report extreme performance issues that can be traced to the size of the reference grid being in the billions, causing memory to be paged, etc. So providing this limit really is necessary. The default is 10,000 rows. I hope that most existing users don’t bump up against that too often. Thenuisance
(ornon.nuisance
) argument inref_grid()
(see below) can help work around this limit. - New
nuisance
option inref_grid()
, by which we can specify names of factors to exclude from the reference grid (accommodating them by averaging) (#282, #292). These must be factors that don’t interact with anything, even other nuisance factors. This provides a remedy for excessive grid sizes. - Improvements to and broadening of
qdrg()
:- Changed the order of arguments in to something a bit more natural
- Default for
contrasts
nowobject$contrasts
whenobject
is specified - Detection of multivariate situations
- Added
ordinal.dim
argument to support ordinal models
- New
force_regular()
function adds invisible rows to an irregularemmGrid
to make it regular (i.e., covers all factor combinations)
Bug fixes and tweaks
- Removed dependency on plyr package (#298)
- Fix to bug in
regrid()
with nested structures (#287) - Fix bug in
rbind()
which mishandled@grid$.offset.
- Major repairs to
clm
andclmm
support to fix issues related to rank deficiency and nested models, particularly withmode = "prob"
(#300) - Allow
type
to be passed inemmeans()
whenobject
is already anemmGrid
(incidentally noticed in #287) - Code to prevent a warning when an existing factor is coerced to a factor in the model formula – see SO question
- Add documentation note for
add_grouping
with multiple reference factors (#291)
emmeans 1.6.3
CRAN release: 2021-08-20
- Clarification of documentation of
ref_grid(object, vcov. = ...)
(#283) - Fix to
emmtrends()
with covariate formulas (#284) - Improved parts of “Basics” vignette - removed “back story”, revised guidance on values and models
- Allow for > 1 reference factor in
add_grouping()
(#286) - Repairs to
contrast()
to avoid all-nonEst
results in irregular nested structures
emmeans 1.6.2
- Fixed navigation error in vignette index
- Discouraging message added to
cld()
results. Also am providing anemm_list
method foremm_list
objects. - Added
mvcontrast()
function (#281) and assoc vignette material - Added
update.summary_emm()
emmeans 1.6.1
CRAN release: 2021-06-01
- Fixed a bug in parsing a response transformation (#274)
- Changed handling of
contrast()
so thatlog2
andlog10
transformations are handled just likelog
. (#273) Also disabled making ratios withgenlog
as it seems ill-advised. - Added support for
log1p
transformation - Improved detection of cases where Tukey adjustment is [in]appropriate (#275)
- Added
type = "scale"
argument toplot.emmGrid()
andemmip()
. This is the same astype = "response"
except the scale itself is transformed (i.e., a log scale if the log transformation was used). Since the same transformation is used, the appearance of the plot will be the same as withtype = "lp"
, but with an altered axis scale. Currently this is implemented only withengine = "ggplot"
. - Fixed bug whereby Scheffe is ignored when there is only one contrast, even though
scheffe.rank
> 1 was specified. (#171) - Added a
subset()
method foremmGrid
objects - Bug fixes for
mcmc
andmcmc.list
objects (#278, #279) -
test()
showsnull
whenever it is nonzero on the chosen scale (#280)
emmeans 1.6.0
CRAN release: 2021-04-24
This version has some changes that affect all users, e.g., not saving .Last.ref_grid
, so we incremented the sub-version number.
- Changed handling of logit transformations in
contrast()
, so that the odds-ratio transformation persists into subsequentcontrast()
calls e.g., interaction contrasts. - We also made
contrast(..., type = ...)
work correctly - Bug fix so that all
p.adjust.methods
work (#267) - Support for
mblogit
extended to work withmmblogit
models (#268) (However, since, mclogit pkg incorporates its own interface) - Added
export
option inprint.emmGrid()
andprint.emm_summary()
- Changed default for
emm_options(save.ref_grid = FALSE)
. Years ago, it seemed potentially useful to save the last reference grid, but this is extra overhead, and writes in the user’s global environment. The option remains if you want it. - Added a note advising against using
as.data.frame
(because we lose potentially important annotations), and information/example on how to see more digits (which I guess is why I’m seeing users do this). - Further refinement to nesting detection. A model like
y ~ A:B
detectedA %in% B
andB %in% A
, and henceA %in% A*B
andB %in% A*B
due to a change in 1.4.6. Now we omit cases where factors are nested in themselves! - Expansion of
cov.reduce
formulas to allow use of custom models for predicting mediating covariates
emmeans 1.5.5
- The
multinom
“correction” in version 1.5.4 was actually an “incorrection.” It was right before, and I made it wrong! If analyzingmultinom
models, use a version other than 1.5.4 - Repairs to support for
mblogit
models - Bug fix for
survreg
support (#258) –survreg()
doesn’t handle missing factor levels the same way aslm()
. This also affects results fromcoxph()
,AER::tobit()
, … - Addition of a note in help
auto.noise
dataset, and changing that example and vignette example to havenoise/10
as the response variable. (Thanks to speech and hearing professor Stuart Rosen for pointing out this issue in an e-mail comment.) - Bug fix for
appx-satterthwaite
mode ingls
/lme
models (#263) - Added
mode = "asymptotic"
forgls
/lme
models. - Added
facetlab
argument toemmip_ggplot()
so user can control how facets are labeled (#261) - Efficiency improvements in
joint_tests()
(#265) - Bug fixes in
joint_tests()
and interaction contrasts for nested models (#266) - Improvement to
multinom
support suggested by this SO question
emmeans 1.5.4
CRAN release: 2021-02-03
- Fix to bug in
rbind.emm_list()
to default forwhich
- Fix for a glitch in recovering data for
gee
models (#249) - Support for
svyglm
objects (#248) - Better support for
lqm
,lqmm
, and added support forrq
&rqs
objects (quantreg package). User may passsummary
orboot
arguments such asmethod
,se
,R
, … (#250) - Correction to
multinom
objects (SEs were previously incorrect) and addition of support for relatedmclogit::mblogit
objects. If at all possible, users should re-run any pre-1.5.4 analyses of multinomial models
Note: This correction was wrong! If using multinomial models, you should use some version other than 1.5.4! - Change to less misleading messages and documentation related to the
N.sim
argument ofregrid()
. We are no longer calling this a posterior sample because this is not really a Bayesian method, it is just a simulated set of regression coefficients.
emmeans 1.5.3
CRAN release: 2020-12-09
- Per long-time threats, we really are removing
CLD()
once and for all. We tried in version 1.5.0, but forced to cave due to downstream problems. - Addition of
levels<-
method that maps toupdate(... levels =)
(#237) - Fix
cld()
so it works with nested cases (#239) - Enable
coef()
method to work with contrasts of nested models. This makes it possible forpwpp()
to work (#239) - Fixed a coding error in
plot()
that occurs if we use `type = “response” but there is in fact no transformation (reported on StackOverflow) - Added
"log10"
and"log2"
as legal transformations inregrid()
- Revised vignette example for MCMC models, added example with bayestestR
- Expanded support for ordinal models to all link functions available in ordinal (errors-out if ordinal not installed and link not available in
stats::make.link()
) - Cleaned-up
emmip()
to route plot output to rendering functionsemmip_ggplot()
andemmip_lattice()
. These functions allow more customization to the plot and can also be called independently. (To do later, maybe next update: the same forplot.emmGrid()
. What to name rendering functions?? – suggestions?) - Cleaned up code for
.emmc
functions so that parenthesization of levels does not get in the way ofref
,exclude
, orinclude
arguments (#246) - Fix to bug in
emtrends()
whendata
is specified (#247) - Tries harder to recover original data when available in the object (#247). In particular, sometimes this is available, e.g., in
$model
slot in alm
object, as long as there are no predictor transformations. This provides a little bit more safety in cases the data have been removed or altered. - Tweaks to
rbind.emm_list()
to allow subsetting. (Also documentation & example)
emmeans 1.5.2
CRAN release: 2020-10-24
- Change to
plot.emmGrid(... comparisons = TRUE)
where we determine arrow bounds and unnecessary-arrow deletions separately in eachby
group. See also Stack Overflow posting -
emmeans()
with contrasts specified ignoresadjust
and passes tocontrast()
instead. Associated documentation improved (I hope) - Bug-fix for missing cases in
plot(..., comparisons = TRUE)
(#228) - Robustified
plot.emmGrid()
so that comparison arrows work correctly with back-transformations. (Previously we usedregrid()
in that case, causing different CIs and PIs depending oncomparisons
) (#230) - Bug fixes in support for
stan_polr
models. - Bug fix for incorrect (and relatively harmless) warning in several models (#234)
- Lower object size via removing unnecessary environment deps (#232)
- Repairs to
as.list()
andas.emmGrid()
to fully support nesting and submodels.
emmeans 1.5.1
CRAN release: 2020-09-18
- Additional checking for potential errors (e.g. memory overload) connected with
submodel
support. Also, much more memory-efficient code therein (#218, #219) - A new option
enable.submodel
so user can switch offsubmodel
support when unwanted or to save memory. -
multinom
support forN.sim
option - Modification to internal dispatching of
recover_data
andemm_basis
so that an external package’s methods are always found and given priority whether or not they are registered (#220) - Patches to
gamlss
support. Smoothers are not supported but other aspects are more reliable. See CV posting - Improvement to auto-detection of transformations (#223)
- Added
aes
argument inpwpp()
for more control over rendering (#178) - Fix to a situation in
plot.emmGrid()
where ordering of factor levels could change depending onCIs
andPIs
(#225)
emmeans 1.5.0
CRAN release: 2020-08-18
- Changed help page for
joint_tests()
to reflectcov.keep
(ver. 1.4.2) -
emm_options()
gains adisable
argument to use for setting aside any existing options. Useful for reproducible bug reporting. - In
emmeans()
with acontr
argument or two-sided formula, we now suppress several particular...
arguments from being passed on tocontrast()
when they should apply only to the construction of the EMMs (#214) - More control of what
...
arguments are passed to methods -
CLD()
was deprecated in version 1.3.4. THIS IS THE LAST VERSION where it will continue to be available. Users should usemultcomp::cld()
instead, for which anemmGrid
method will continue to exist. - Experimental
submodel
option- Bug fix therein (#217)
- Enhancements to
mgcv::gam
support (#216) - New
ubds
dataset for testing with messy situations - Added minimal support for
lqm
andlqmm
models (#213) - Interim support for user-supplied contrasts for
stanreg
models (#212)
emmeans 1.4.8
CRAN release: 2020-06-26
- Bug fix and smoother support for
stanreg
objects (#202) - Fix to
emmip()
to be consistent between one curve and several, in whether points are displayed (style
option) - Added
"scale"
option tomake.tran()
- Auto-detection of standardized response transformation
- Fix to a scoping issue in
emtrends()
(#201) - Bug fix for #197 created a new issue #206. Both now fixed.
- Non-existent reference levels in
trt.vs.ctrl.emmc()
now throws an error (#208) - Added a default for
linfct
(the identity) toemmobj
- Provisions for more flexible and consistent labeling/naming of results. This includes added
emm_options
"sep"
and"parens"
, and aparens
argument incontrast()
.sep
controls how factor levels are combined when ploted or contrasted, andparens
sets whether, what, and how labels are parenthesized incontrast()
. In constructing contrasts of contrasts, for example, labels likeA - B - C - D
are now(A - B) - (C - D)
, by default. To reproduce old labeling, do `emm_options(sep = “,”, parens = “a^”)
emmeans 1.4.7
CRAN release: 2020-05-25
- Repairs to
pwpp()
so it plays nice with nonestimable cases - Added
"xplanations"
vignette with additional documentation on methods used. (comparison arrows, for starters) - Touch-ups to
plot()
, especially regarding comparison arrows - Bug fix for
stanreg
models (#196) - Fixed error in
emmeans(obj, "1", by = "something")
(#197) -
eff_size()
now supportsemm_list
objects with a$contrasts
component, using those contrasts. This helps those who specifypairwise ~ treatment
. - Labels in
contrast()
for factor combinations withby
groups were wacky (#199) -
emtrends()
screwed up with multivariate models (#200). - Added a new argument
calc
tosummary()
. For example,calc = c(n = ~.wgt.)
will add a column of sample sizes to the summary.
emmeans 1.4.6
CRAN release: 2020-04-19
- Improvements to
coxph
support for models with strata -
emmeans()
withspecs
of classlist
now passes anyoffset
andtrend
arguments (#179) - Added
plim
argument topwpp()
to allow controlling the scale - More documentation on using
params
(#180) - Robustified support for
gls
objects when data are incomplete (#181) - Fixed bug in
joint_tests()
andtest(..., joint = TRUE)
that can occur with nontrivial@dffun()
slots (#184) - Improved support for Satterthwaite-based methods in
gls
(#185) and renamedboot-satterthwaite
toappx-satterthwaite
(#176) - Further repairs to nesting-related code (#186)
- Fix
transform
argument inref_grid()
so it is same as inregrid()
(#188) - Added
pwpm()
function for displaying estimates, pairwise comparisons, and P values in matrix form
emmeans 1.4.5
CRAN release: 2020-03-04
- Change to
.all.vars()
that addresses #170 - Addition of hidden argument
scheffe.rank
insummary.emmGrid()
to manually specify the desired dimensionality of a Scheffe adjustment (#171) - Provided for
...
to be included inoptions
in calls toemmeans()
andcontrast()
. This allows passing anysummary()
argument more easily, e.g.,emmeans(..., type = "response", bias.adjust = TRUE, infer = c(TRUE, TRUE))
(Before, we would have had to wrap this insummary()
) - Added a
plotit
argument toplot.emmGrid()
that works similarly to that inemmip()
. - Removed startup message for behavior change in 1.4.2; it’s been long enough.
- Fixed bug with
character predictors in
at` (#175)
emmeans 1.4.4
CRAN release: 2020-01-28
- Fixed bug in
emmeans()
associated with non-factors such asDate
(#162) - Added
nesting.order
option toemmip()
(#163) - New
style
argument foremmip()
allows plotting on a numeric scale - More robust detection of response transformations (#166)
- Ensure
pwpp()
has tick marks on P-value axis (#167) - Bug fix for
regrid()
for error when estimates exceed bounds - Bug fix in auto-detecting nesting (#169) to make it less “enthusiastic”
- Fixes to formula operations needed because
formula.tools:::as.character.formula
messes me up (thanks to Berwin Turloch, UWA, for alerting me) - Making
dqrg()
more visible in the documentation (because it’s often useful) - Added more methods for
emm_list
objects, e.g.rbind()
andas.data.frame()
,as.list()
, andas.emm_list()
emmeans 1.4.3.01
CRAN release: 2019-11-28
- Fixed bug in post-grid support that affects, e.g., the ggeffects package (#161)
emmeans 1.4.3
CRAN release: 2019-11-26
- Added
"bcnPower"
option tomake.tran()
(percar::bcnPower()
) - Scoping correction for
emmtrends()
(#153) - Allow passing
...
to hook functions (need exposed by #154) - Addition to
regrid()
whereby we can fake any response transformation – not just"log"
(again inspired by #154) - Informative message when pbkrtest or lmerTest is not found (affects
merMod
objects) (#157) - Change in
pwpp()
to make extremely small P values more distinguishable
emmeans 1.4.2
CRAN release: 2019-10-24
- First argument of
emtrends()
is nowobject
, notmodel
, to avoid potential mis-matching of the latter with optionalmode
argument -
emtrends()
now uses more robust and efficient code whereby a single reference grid is constructed containing all needed values ofvar
. The old version could fail, e.g., in cases where the reference grid involves post-processing. (#145) - Added
scale
argument tocontrast()
- Added new
"identity"
contrast method - New
eff_size()
function for Cohen effect sizes - Expanded capabilities for interaction contrasts (#146)
- New
cov.keep
argument inref_grid()
for specifying covariates to be treated just like factors (#148). A side effect is that the system default for indicator variables as covariates is to treat them like 2-level factors. This could change the results obtained from some analyses using earlier versions. To replicate old analyses, setemm_options(cov.keep = character(0))
. - Added merMod-related options as convenience arguments (#150)
- Bug fixes:
regrid
ignored offsets with Bayesian models;emtrends()
did not supplyoptions
andmisc
arguments toemm_basis()
(#143)
emmeans 1.4.1
CRAN release: 2019-09-12
- Added non-estimability infrastructure for Bayesian models,
stanreg
in particular (#114) - Added
max.degree
argument inemtrends()
making it possible to obtain higher-order trends (#133). Plus minor tuneups, e.g., smaller default increment for difference quotients - Made
emmeans()
more forgiving with ’byvariables; e.g.,
emmeans(model, ~ dose | treat, by = “route”)will find both
byvariables whereas previously
“route”` would be ignored. - Temporary fix for glitch in gls support where Satterthwaite isn’t always right.
- Attempt to make annotations clearer and more consistent regarding degrees-of-freedom methods.
- Provisions whereby externally provided
emm_basis()
andrecover_data()
methods are used in preference to internal ones - so package developers can provide improvements over what I’ve cobbled together. - Tried to produce more informative message when
recover_data()
fails - Fixed bug in
contrast()
in identifying true contrasts (#134) - Fixed a bug in
plot.summary_emm()
regardingCIs
andintervals
(#137) - Improved support for response transformations. Models with formulas like like
log(y + 1) ~ ...
and2*sqrt(y + 0.5) ~ ...
are now auto-detected. [This may cause discrepancies with examples in past usages, but if so, that would be because the response transformation was previously incorrectly interpreted.] - Added a
ratios
argument tocontrast()
to decide how to handlelog
andlogit
- Added message/annotation when contrasts are summarized with
type = "response"
but there is no way to back-transform them (or we opted out withratios = FALSE
)
emmeans 1.4
CRAN release: 2019-08-01
- Added a courtesy function
.emm_register()
to make it easier for other packages to register their emmeans support methods - Clarified the “confidence intervals” vignette discussion of
infer
, explaining that Bayesian models are handled differently (#128) - Added
PIs
option toplot.emmGrid()
andemmip()
(#131). Also, inplot.emmGrid()
, theintervals
argument has been changed toCIs
for sake of consistency and less confusion;intervals
is still supported for backaward compatibility. -
plot.emmGrid
gains acolors
argument so we can customize colors used. - Bug fix for
glht
support (#132 contributed by Balsz Banfai) -
regrid
gainssim
andN.sim
arguments whereby we can generate a fake posterior sample from a frequentist model.
emmeans 1.3.5.1
CRAN release: 2019-06-26
- Bug fix for
gls
objects with non-matrixapVar
member (#119) - Repairs faulty links in 1.3.5 vignettes
emmeans 1.3.5
CRAN release: 2019-06-10
- First steps to take prediction seriously. This includes
- Addition of a
sigma
argument toref_grid()
(defaults tosigma(object)
if available) - Addition of an
interval
argument inpredict.emmGrid()
- Addition of a
likelihood
argument inas.mcmc
to allow for simulating from the posterior predictive distribution - Crude provisions for bias adjustment when back-transforming. This is not really prediction, but it is made possible by availability of
sigma
in object
- Addition of a
- Further steps to lower the profile of
cld()
andCLD()
- Family size for Tukey adjustment was wrong when using
exclude
(#107) - Provided for direct passing of info from
recover_data
toemm_basis
- Attempts to broaden
MCMCglmm
support
emmeans 1.3.4
CRAN release: 2019-04-21
- Un-naming a lot of arguments in
do.call(paste, ...)
anddo.call(order, ...)
, to prevent problems with factor names likemethod
that are argument names for these functions (#94) - Fix to a logic error in
summary.emmGrid()
whereby transformations of classlist
were ignored. - Enhancement to
update.emmGrid(..., levels = levs)
whereby we can easily relabel the reference grid and ensure that thegrid
androles
slots stay consistent. Added vignette example. - Clarified ordering rules used by
emmeans()
. We now ensure that the original order of the reference grid is preserved. Previously, the grid was re-ordered if any numeric or character levels occurred out of order, perorder()
- Curbing use of “statistical significance” language. This includes additional vignette material and plans to deprecate
CLD()
due to its misleading display of pairwise-comparison tests. - Bug fix for
betareg
objects, where the wrongterms
component was sometimes used. - Correction to logic error that affected multiplicity adjustments when
by
variables are present (#98). - Addition of
pwpp()
function to plot P values of comparisons - Improvement to
summary(..., adjust = "scheffe")
. We now actually compute and use the rank of the matrix of linear functions to obtain the F numerator d.f., rather than trying to guess the likely correct value. - Removal of vignette on transitioning from lsmeans – it’s been a long enough time now.
emmeans 1.3.3
CRAN release: 2019-03-02
- Fix to unintended consequence of #71 that caused incorrect ordering of
contrast()
results if they are later used byemmeans()
. This was first noticed with ordinal models inprob
mode (#83). - Improved checking of conformability of parameters – for models with rank deficiency not handled same way as lm()’s NA convention
- Added basic support for
sommer::mmer
,MuMIn::averaging
, andmice::mira
objects - Fix in
nnet::multinom
support when there are 2 outcomes (#19) - Added Satterthwaite d.f. to
gls
objects -
famSize
now correct whenexclude
orinclude
is used in a contrast function (see #68) - Stronger warnings of possible bias with
aovList
objects, in part due to the popularity ofafex::aov_ez()
which uses these models. - Updates to FAQs vignette
emmeans 1.3.2
CRAN release: 2019-01-22
- I decided to enable “optimal digits” display by default. In summaries, we try to show enough—but not too much—precision in estimates and confidence intervals. If you don’t like this and want to revert to the old (exaggerated precision) behavior, do
emm_options(opt.digits = FALSE)
- Added
include
argument to most.emmc
functions (#67) - Now allow character values for
ref
,exclude
, andinclude
in.emmc
functions (#68) - Better handling of matrix predictors (#66)
- Fixed over-zealous choice to not pass
...
arguments inemmeans()
when two-sided formulas are present - Fix to
clm
support when model is rank-deficient - Fix to
regrid(..., transform = "log")
error when there are existing non-estimable cases (issue #65) - Improvements to
brmsfit
support (#43) - Added support for
mgcv::gam
andmgcv::gamm
models -
.my.vcov()
now passes...
to clients - Removed glmmADMB support. This package appears to be dormant
- Fixed ordering bug for nested models (#71)
- Support for
manova
object no longer requiresdata
keyword (#72) - Added support for multivariate response in
aovlist
models (#73) - Documentation clarification (#76)
- Fix to
CLD
fatal error whensort = TRUE
(#77) - Fix to issue with weights and incomplete cases with
lme
objects (#75) - Nested fixed-effects yielded NonEsts when two factors are nested in the same factor(s) (#79)
emmeans 1.3.1
CRAN release: 2018-12-13
-
"mvt"
adjustment ignoredby
grouping -
contrast()
mis-labeled estimates when levels varied amongby
groups (most prominently this happened inCLD(..., details = TRUE)
) - Changed
aovlist
support so it re-fits the model when non-sum-to-zero contrasts were used -
print.summary_emm()
now cleans up numeric columns withzapsmall()
- More robust handling of
nesting
inref_grid()
andupdate()
, and addition ofcovnest
argument for whether to include covariates when auto-detecting nesting - Revision of some vignettes
- Fixed bug in
hpd.summary()
and handoff to it fromsummary()
- Fixed bug where
ref_grid()
ignoredmult.levs
- Fixes in emmeans where it passes
...
where it shouldn’t -
CLD()
now works for MCMC models (uses frequentist summary) - Addition of
opt.digits
option
emmeans 1.3.0
CRAN release: 2018-10-26
- Deprecated functions like
ref.grid()
put to final rest, and we no longer support packages that providerecover.data
orlsm.basis
methods - Courtesy exports
.recover_data()
and.emm_basis()
to provide access for extension developers to all available methods - Streamlining of a stored example in
inst/extdata
- Fix to
.all.vars()
that could cause errors when response variable has a function call with character constants. - Relabeling of differences as ratios when appropriate in
regrid()
(so results matchsummary()
labeling withtype = "response"
). -
plot.emmGrid(..., comparisons = TRUE, type = "response")
produced incorrect comparison arrows; now fixed
emmeans 1.2.4
CRAN release: 2018-09-22
- Support for model formulas such as
df$y ~ df$treat + df[["cov"]]
. This had failed previously for two obscure reasons, but now works correctly. - New
simplify.names
option for above types of models -
emm_options()
with no arguments now returns all options in force, including the defaults. This makes it more consistent withoptions()
- Bug fix for
emtrends()
; produced incorrect results in models with offsets. - Separated the help pages for
update.emmGrid()
andemm_options()
- New
qdrg()
function (quick and dirty reference grid) for help with unsupported model objects
emmeans 1.2.3
CRAN release: 2018-07-18
- S3 methods involving packages multcomp and coda are now dynamically registered, not merely exported as functions. This passes checks when S3 methods are required to be registered.
-
cld()
has been deprecated in favor ofCLD()
. This had been a headache. multcomp is the wrong place for the generic to be; it is too fancy a dance to exportcld
with or without having multcomp installed. - Added vignette caution regarding interdependent covariates
- Improved glmmADMB support to recover contrasts correctly
emmeans 1.2.2
CRAN release: 2018-06-26
- Removed ggplot2, multcomp, and coda to Suggests – thus vastly reducing dependencies
- Added a FAQ to the FAQs vignette
- Modified advice in
xtending.Rmd
vignette on how to export methods - Fixes to
revpairwise.emmc
andcld
regarding comparing only 1 EMM -
cld.emm_list
now returns results only forobject[[ which[1] ]]
, along with a warning message. - Deprecated
emmeans
specs likecld ~ group
, a vestige of lsmeans as it did not work correctly (and was already undocumented)
emmeans 1.2
CRAN release: 2018-05-08
- Index of vignette topics added
- New, improved (to my taste) vignette formats
- Fixed df bug in regrid (#29)
- Fixed annotation bug for nested models (#30)
- Better documentation for
lme
models in “models” vignette - Additional fixes for arguments passed to
.emmc
functions (#22) - Support added for logical predictors (who knew we could have those? not me)
- Replaced tex/pdf “Extending” vignette with Rmd/html
- Overhauled the faulty logic for df methods in emm_basis.merMod
- Added Henrik to contributors list (long-standing oversight)
- Added
exclude
argument to most.emmc
functions: allows user to omit certain levels when computing contrasts - New
hpd.summary()
function for Bayesian models to show HPD intervals rather than frequentist summary. Note:summary()
automatically reroutes to it. Alsoplot()
andemmip()
play along. - Rudimentary support for brms package
-
Ad hoc Satterthwaite method for
nlme::lme
models
emmeans 1.1.3
CRAN release: 2018-04-01
- Formatting corrections in documentation
- Fixed bug for survival models where
Surv()
was interpreted as a response transformation. - Fixed bug (issue #19) in multinom support
- Fixed bug (issue #22) in optional arguments with interaction contrasts
- Fixed bug (issue #23) in weighting with character predictors
- Clarifying message when
cld()
is applied to anemm_list
(issue #24) - Added
offset
argument toref_grid()
(scalar offset only) and toemmeans()
(vector offset allowed) – (issue #18) - New optional argument for
[.summary_emm
to choose whether to retain its class or coerce to adata.frame
(relates to issue #14) - Added
reverse
option fortrt.vs.ctrl
and relatives (#27)
emmeans 1.1.2
CRAN release: 2018-02-24
- Changed the way
terms
is accessed withlme
objects to make it more robust -
emmeans:::convert_scripts()
renames output file more simply - Added
[
method for classsummary_emm
- Added
simple
argument forcontrast
- essentially the complement ofby
- Improved estimability handling in
joint_tests()
- Made
ref_grid()
acceptylevs
list of length > 1; also slight argument change:mult.name
->mult.names
- Various bug fixes, bullet-proofing
- Fixes to make Markdown files render better
emmeans 1.1
CRAN release: 2018-01-10
- Fixed a bug in
emmeans()
whereinweights
was ignored whenspecs
is alist
- Coerce
data
argument, if supplied to a data.frame (recover_data()
doesn’t like tibbles…) - Added
as.data.frame
method foremmGrid
objects, making it often possible to pass it directly to other functions as adata
argument. - Fixed bug in
contrast()
whereby
was ignored for interaction contrasts - Fixed bug in
as.glht()
where it choked ondf = Inf
- Fixed bug occurring when a model call has no
data
orsubset
- New
joint_tests()
function tests all [interaction] contrasts
emmeans 1.0
CRAN release: 2017-12-05
- Added preliminary support for
gamlss
objects (but doesn’t support smoothing). Additional argument iswhat = c("mu", "sigma", "nu", "tau")
It seems to be flaky when the model of interest is just~ 1
. - Improved support for models with fancy variable names (containing spaces and such)
- Fixed a bug whereby
emmeans()
might passdata
tocontrast()
- Added some missing documentation for
summary.emmGrid()
- Repaired handling of
emm_options(summary = ...)
to work as advertised. - Changed many object names in examples and vignettes from xxx.emmGrid to xxx.emm (result of overdoing the renaming the object class itself)
- Changed
emmGrid()
function toemm()
as had been intended as alternative tomcp()
inmultcomp::glht()
(result of ditto). - Fixed error in exporting
cld.emm_list()
- Fixed a bug whereby all CIs were computed using the first estimate’s degrees of freedom.
- Now using
Inf
to display d.f. for asymptotic (z) tests. (NA
will still work too butInf
is a better choice for consistency and meaning.) - Bug fix in nesting-detection code when model has only an intercept
emmeans 0.9.1
CRAN release: 2017-11-05
- Documentation corrections (broken links, misspellings, mistakes)
- More sophisticated check for randomized data in
recover_data()
now throws an error when it finds recovered data not reproducible - Added support for gam::gam objects
- Fixes to
vcov()
calls to comply with recent R-devel changes
emmeans 0.9
CRAN release: 2017-10-20
This is the initial major version that replaces the lsmeans package. Changes shown below are changes made to the last real release of lsmeans (version 2.27-2). lsmeans versions greater than that are transitional to that package being retired.
- We now emphasize the terminology “estimated marginal means” rather than “least-squares means”
- The flagship functions are now
emmeans()
,emtrends()
,emmip()
, etc. Butlsmeans()
,lstrends()
, etc. as well aspmmeans()
etc. are mapped to their correspondingemxxxx()
functions. - In addition, we are trying to avoid names that could get confused as S3 methods. So,
ref.grid -> ref_grid
,lsm.options -> emm_options
, etc. - Classes
ref.grid
andlsmobj
are gone. Both are replaced by classemmGrid
. Anas.emmGrid()
function is provided to convert old objects to classemmGrid
. - I decided to revert back to “kenward-roger” as the default degrees-of-freedom method for
lmerMod models
. Also added optionsdisable.lmerTest
andlmerTest.limit
, similar to those for pbkrtest. - Documentation and NAMESPACE are now “ROxygenated”
- Additional
neuralgia
andpigs
datasets - Dispatching of
emmmeans()
methods is now top-down rather than convoluted intermingling of S3 methods - Improved display of back-transformed contrasts when log or logit transformation was used: We change any
-
s in labels to/
s to emphasize that thnese results are ratios. - A message is now displayed when nesting is auto-detected in
ref_grid
. (Can be disabled viaemm_options()
) - Options were added for several messages that users may want to suppress, e.g., ones about interactions and nesting.
- Greatly overhauled help page for models. It is now a vignette, with a quick reference chart linked to details, and is organized by similarities instead of packages.
- Support for ‘mer’ objects (lme4.0 package) removed.
- A large number of smaller interlinked vignettes replaces the one big one on using the package. Several vignettes are linked in the help pages.
- Graphics methods
plot()
andemmip()
are now ggplot2-based. Old lattice-based functionality is still available too, and there is agraphics.engine
option to choose the default. - Non-exported utilities convert_workspace() and convert_scripts() to help with transition
- Moved
Suggests
pkgs toEnhances
when not needed for building/testing