Hi Rune,
thanks a lot for your quick upgrade. I just uploaded the new version to Debian.
Kind regards
Andreas.
On Mon, Feb 11, 2019 at 05:21:54PM +0100, Rune Christensen wrote:
> Dear all,
>
> This is currently being fixed and a new version of lmerTest is on its way to
> CRAN, cf. https://cran.r-project.org/package=lmerTest
> <https://cran.r-project.org/package=lmerTest>
>
> The latest version of lme4 was released to CRAN without our knowledge and
> that version caused lmerTest to fail its tests on most platforms (mostly
> because the new default optimiser is much less accurate than the old default
> optimiser, cf. https://github.com/lme4/lme4/issues/501
> <https://github.com/lme4/lme4/issues/501>). After being notified of the
> problems we have updated lmerTest as soon as possible.
>
> BR
> Rune
>
> > On 11 Feb 2019, at 07.39, Per B. Brockhoff <[email protected]> wrote:
> >
> > Sendt fra min iPhone
> >
> > Start på videresendt besked:
> >
> >> Fra: Andreas Tille <[email protected] <mailto:[email protected]>>
> >> Dato: 10. februar 2019 kl. 16.07.12 CET
> >> Til: Paul Gevers <[email protected] <mailto:[email protected]>>,
> >> <[email protected] <mailto:[email protected]>>, "Per Bruun
> >> Brockhoff" <[email protected] <mailto:[email protected]>>
> >> Emne: Vedr.: Bug#921938: lme4 breaks r-cran-lmertest autopkgtest
> >>
> >> Hi again,
> >>
> >> may be you get all the relevant information directly from CRAN:
> >>
> >> https://cloud.r-project.org/web/checks/check_results_lmerTest.html
> >> <https://cloud.r-project.org/web/checks/check_results_lmerTest.html>
> >>
> >> Kind regards
> >>
> >> Andreas.
> >>
> >> On Sun, Feb 10, 2019 at 03:44:55PM +0100, Andreas Tille wrote:
> >>> Control: tags -1 help upstream
> >>> Control: forwarded -1 Per Bruun Brockhoff <[email protected]
> >>> <mailto:[email protected]>>
> >>>
> >>> Hi Per,
> >>>
> >>> the Debian packaged version of lmerTest seems to show issues with the
> >>> latest version of lme4. From your insight into lmerTest can you give
> >>> some hint about possible reasons for this incompatibility?
> >>>
> >>> Kind regards
> >>>
> >>> Andreas.
> >>>
> >>> PS: Please let me know whether you need further information.
> >>>
> >>> On Sun, Feb 10, 2019 at 01:35:53PM +0100, Paul Gevers wrote:
> >>>> Source: lme4, r-cran-lmertest
> >>>> Control: found -1 lme4/1.1-20-1
> >>>> Control: found -1 r-cran-lmertest/3.0-1-2
> >>>> Severity: important
> >>>> X-Debbugs-CC: [email protected]
> >>>> <mailto:[email protected]>
> >>>> User: [email protected] <mailto:[email protected]>
> >>>> Usertags: breaks needs-update
> >>>>
> >>>> Dear maintainers,
> >>>>
> >>>> With a recent upload of lme4 the autopkgtest of r-cran-lmertest fails in
> >>>> testing when that autopkgtest is run with the binary packages of lme4
> >>>> from unstable. It passes when run with only packages from testing. In
> >>>> tabular form:
> >>>> pass fail
> >>>> lme4 from testing 1.1-20-1
> >>>> r-cran-lmertest from testing 3.0-1-2
> >>>> all others from testing from testing
> >>>>
> >>>> I copied some of the output at the bottom of this report.
> >>>>
> >>>> Currently this regression is blocking the migration of lme4 to testing
> >>>> [1]. Due to the nature of this issue, I filed this bug report against
> >>>> both packages. Can you please investigate the situation and reassign the
> >>>> bug to the right package? If needed, please change the bug's severity.
> >>>>
> >>>> More information about this bug and the reason for filing it can be
> >>>> found on
> >>>> https://wiki.debian.org/ContinuousIntegration/RegressionEmailInformation
> >>>> <https://wiki.debian.org/ContinuousIntegration/RegressionEmailInformation>
> >>>>
> >>>> Paul
> >>>>
> >>>> [1] https://qa.debian.org/excuses.php?package=lme4
> >>>> <https://qa.debian.org/excuses.php?package=lme4>
> >>>>
> >>>> https://ci.debian.net/data/autopkgtest/testing/amd64/r/r-cran-lmertest/1896879/log.gz
> >>>>
> >>>> <https://ci.debian.net/data/autopkgtest/testing/amd64/r/r-cran-lmertest/1896879/log.gz>
> >>>>
> >>>> autopkgtest [04:42:34]: test run-unit-test: [-----------------------
> >>>> BEGIN TEST test_a_utils.R
> >>>>
> >>>> R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
> >>>> Copyright (C) 2018 The R Foundation for Statistical Computing
> >>>> Platform: x86_64-pc-linux-gnu (64-bit)
> >>>>
> >>>> R is free software and comes with ABSOLUTELY NO WARRANTY.
> >>>> You are welcome to redistribute it under certain conditions.
> >>>> Type 'license()' or 'licence()' for distribution details.
> >>>>
> >>>> R is a collaborative project with many contributors.
> >>>> Type 'contributors()' for more information and
> >>>> 'citation()' on how to cite R or R packages in publications.
> >>>>
> >>>> Type 'demo()' for some demos, 'help()' for on-line help, or
> >>>> 'help.start()' for an HTML browser interface to help.
> >>>> Type 'q()' to quit R.
> >>>>
> >>>>> # test_a_utils.R
> >>>>>
> >>>>> library(lmerTest)
> >>>> Loading required package: lme4
> >>>> Loading required package: Matrix
> >>>>
> >>>> Attaching package: 'lmerTest'
> >>>>
> >>>> The following object is masked from 'package:lme4':
> >>>>
> >>>> lmer
> >>>>
> >>>> The following object is masked from 'package:stats':
> >>>>
> >>>> step
> >>>>
> >>>>>
> >>>>> # test safeDeparse() - equivalence and differences to deparse():
> >>>>> deparse_args <- formals(deparse)
> >>>>> safeDeparse_args <- formals(lmerTest:::safeDeparse)
> >>>>> stopifnot(
> >>>> + all.equal(names(deparse_args), names(safeDeparse_args)),
> >>>> + all.equal(deparse_args[!names(deparse_args) %in% c("control",
> >>>> "width.cutoff")],
> >>>> + safeDeparse_args[!names(safeDeparse_args) %in%
> >>>> c("control", "width.cutoff")]),
> >>>> + all.equal(deparse_args[["width.cutoff"]], 60L),
> >>>> + all(eval(safeDeparse_args[["control"]]) %in%
> >>>> eval(deparse_args[["control"]])),
> >>>> + all.equal(safeDeparse_args[["width.cutoff"]], 500L)
> >>>> + )
> >>>>>
> >>>>>
> >>>> BEGIN TEST test_anova.R
> >>>>
> >>>> R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
> >>>> Copyright (C) 2018 The R Foundation for Statistical Computing
> >>>> Platform: x86_64-pc-linux-gnu (64-bit)
> >>>>
> >>>> R is free software and comes with ABSOLUTELY NO WARRANTY.
> >>>> You are welcome to redistribute it under certain conditions.
> >>>> Type 'license()' or 'licence()' for distribution details.
> >>>>
> >>>> R is a collaborative project with many contributors.
> >>>> Type 'contributors()' for more information and
> >>>> 'citation()' on how to cite R or R packages in publications.
> >>>>
> >>>> Type 'demo()' for some demos, 'help()' for on-line help, or
> >>>> 'help.start()' for an HTML browser interface to help.
> >>>> Type 'q()' to quit R.
> >>>>
> >>>>> # test_anova.R
> >>>>> library(lmerTest)
> >>>> Loading required package: lme4
> >>>> Loading required package: Matrix
> >>>>
> >>>> Attaching package: 'lmerTest'
> >>>>
> >>>> The following object is masked from 'package:lme4':
> >>>>
> >>>> lmer
> >>>>
> >>>> The following object is masked from 'package:stats':
> >>>>
> >>>> step
> >>>>
> >>>>>
> >>>>> # WRE says "using if(requireNamespace("pkgname")) is preferred, if
> >>>> possible."
> >>>>> # even in tests:
> >>>>> assertError <- function(expr, ...)
> >>>> + if(requireNamespace("tools")) tools::assertError(expr, ...) else
> >>>> invisible()
> >>>>> assertWarning <- function(expr, ...)
> >>>> + if(requireNamespace("tools")) tools::assertWarning(expr, ...) else
> >>>> invisible()
> >>>>>
> >>>>> # Kenward-Roger only available with pbkrtest and only then validated
> >>>> in R >= 3.3.3
> >>>>> # (faulty results for R < 3.3.3 may be due to unstated dependencies in
> >>>> pbkrtest)
> >>>>> has_pbkrtest <- requireNamespace("pbkrtest", quietly = TRUE) &&
> >>>> getRversion() >= "3.3.3"
> >>>>>
> >>>>> data("sleepstudy", package="lme4")
> >>>>> TOL <- 1e-4
> >>>>>
> >>>>> ####################################
> >>>>> ## Basic anova tests
> >>>>> ####################################
> >>>>>
> >>>>> m <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
> >>>>>
> >>>>> ####### ddf argument:
> >>>>> (an1 <- anova(m)) # Also testing print method.
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, ddf="Satterthwaite"))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2b <- anova(m, ddf="Satterthwaite", type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2c <- anova(m, ddf="Satterthwaite", type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>> (an3 <- anova(m, ddf="Sat")) ## Abbreviated argument
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an3, tolerance=TOL)
> >>>> + ))
> >>>>> if(has_pbkrtest) {
> >>>> + (anova(m, ddf="Kenward-Roger"))
> >>>> + (anova(m, ddf="Kenward-Roger", type=3))
> >>>> + }
> >>>> Type III Analysis of Variance Table with Kenward-Roger's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 17 45.843 3.268e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an1 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> Days 1 30024 30024 45.843
> >>>>> (an2 <- anova(m, ddf="lme4", type=3)) # 'type' is ignored with
> >>>>> ddf="lme4"
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> Days 1 30024 30024 45.843
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>> res <- assertError(anova(m, ddf="KR")) ## Error on incorrect arg.
> >>>>> stopifnot(
> >>>> + grepl("'arg' should be one of ", unlist(res[[1]])$message)
> >>>> + )
> >>>>>
> >>>>> ## lme4 method:
> >>>>> an1 <- anova(m, ddf="lme4")
> >>>>> an2 <- anova(as(m, "lmerMod"))
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>>
> >>>>> ###### type argument:
> >>>>> (an1 <- anova(m, type="1")) # valid type arg.
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type="I")) # same
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>> (an3 <- anova(m, type=1)) # Not strictly valid, but accepted
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an3, tolerance=TOL)
> >>>> + ))
> >>>>>
> >>>>> (an1 <- anova(m, type="2")) # valid type arg.
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type="II")) # same
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>> (an3 <- anova(m, type=3)) # Not strictly valid, but accepted
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an3, check.attributes=FALSE, tolerance=TOL)
> >>>> + ))
> >>>>>
> >>>>> (an1 <- anova(m, type="3")) # valid type arg.
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type="III")) # same
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an2, tolerance=TOL)
> >>>> + ))
> >>>>> (an3 <- anova(m, type=3)) # Not strictly valid, but accepted
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 30024 30024 1 16.995 45.843 3.273e-06 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(isTRUE(
> >>>> + all.equal(an1, an3, tolerance=TOL)
> >>>> + ))
> >>>>> assertError(anova(m, type=0)) # Not valid arg.
> >>>>> assertError(anova(m, type="i")) # Not valid arg.
> >>>>>
> >>>>> ####### Model comparison:
> >>>>> fm <- lm(Reaction ~ Days, sleepstudy)
> >>>>> (an <- anova(m, fm))
> >>>> refitting model(s) with ML (instead of REML)
> >>>> Data: sleepstudy
> >>>> Models:
> >>>> fm: Reaction ~ Days
> >>>> m: Reaction ~ Days + (Days | Subject)
> >>>> Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
> >>>> fm 3 1906.3 1915.9 -950.15 1900.3
> >>>> m 6 1763.9 1783.1 -875.97 1751.9 148.35 3 < 2.2e-16 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(
> >>>> + nrow(an) == 2L,
> >>>> + rownames(an)[2] == "m"
> >>>> + )
> >>>>>
> >>>>> m2 <- lmer(Reaction ~ Days + I(Days^2) + (Days | Subject), sleepstudy)
> >>>>> (an <- anova(m, m2, refit=FALSE))
> >>>> Data: sleepstudy
> >>>> Models:
> >>>> m: Reaction ~ Days + (Days | Subject)
> >>>> m2: Reaction ~ Days + I(Days^2) + (Days | Subject)
> >>>> Df AIC BIC logLik deviance Chisq Chi Df Pr(>Chisq)
> >>>> m 6 1755.6 1774.8 -871.81 1743.6
> >>>> m2 7 1756.8 1779.2 -871.41 1742.8 0.8127 1 0.3673
> >>>>> stopifnot(
> >>>> + nrow(an) == 2L,
> >>>> + rownames(an)[1] == "m"
> >>>> + )
> >>>>>
> >>>>>
> >>>>> ####################################
> >>>>> ## Example with factor fixef:
> >>>>> ####################################
> >>>>>
> >>>>> ## 'temp' is continuous, 'temperature' an ordered factor with 6 levels
> >>>>> data("cake", package="lme4")
> >>>>> m <- lmer(angle ~ recipe * temp + (1|recipe:replicate), cake)
> >>>>> (an <- anova(m))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.00 2.00 2 254.02 0.0957 0.9088
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> recipe 2 10.39 5.20 0.2488
> >>>> temp 1 1966.71 1966.71 94.1632
> >>>> recipe:temp 2 1.74 0.87 0.0417
> >>>>>
> >>>>> if(has_pbkrtest) {
> >>>> + (an_KR <- anova(m, ddf="Kenward-Roger"))
> >>>> + # res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + # an_lme4[, c("Sum Sq", "Mean Sq", "F value")])
> >>>> + # stopifnot(isTRUE(res))
> >>>> + res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_KR[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>> + stopifnot(isTRUE(res))
> >>>> + }
> >>>>> stopifnot(all.equal(c(2, 1, 2), an$NumDF, tol=1e-6),
> >>>> + all.equal(c(254.0157612, 222, 222), an$DenDF, tol=TOL))
> >>>>>
> >>>>> an3 <- anova(m, type=3)
> >>>>> an2 <- anova(m, type=2)
> >>>>> an1 <- anova(m, type=1)
> >>>>>
> >>>>> ## Data is balanced, so Type II and III should be identical:
> >>>>> ## One variable is continuous, so Type I and II/III are different:
> >>>>> stopifnot(
> >>>> + isTRUE(all.equal(an3, an2, check.attributes=FALSE, tolerance=TOL)),
> >>>> + !isTRUE(all.equal(an1, an2, check.attributes=FALSE, tolerance=1e-8))
> >>>> + )
> >>>>>
> >>>>> # Using an ordered factor:
> >>>>> m <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), cake)
> >>>>> (an1 <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> # Type 3 is also available with ordered factors:
> >>>>> (an3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> ## Balanced data and only factors: Type I, II and III should be the
> >>>>> same:
> >>>>> stopifnot(
> >>>> + isTRUE(all.equal(an1, an2, check.attributes=FALSE, tolerance=TOL)),
> >>>> + isTRUE(all.equal(an1, an3, check.attributes=FALSE, tolerance=TOL))
> >>>> + )
> >>>>>
> >>>>> (an <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_lme4 <- anova(m, type=1, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> recipe 2 10.19 5.09 0.2488
> >>>> temperature 5 2100.30 420.06 20.5199
> >>>> recipe:temperature 10 205.98 20.60 1.0062
> >>>>> res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_lme4[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>>> stopifnot(isTRUE(res))
> >>>>> if(has_pbkrtest) {
> >>>> + (an_KR <- anova(m, type=1, ddf="Kenward-Roger"))
> >>>> + res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_KR[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>> + stopifnot(isTRUE(res))
> >>>> + }
> >>>>> stopifnot(all.equal(c(2, 5, 10), an$NumDF, tolerance=TOL),
> >>>> + all.equal(c(42, 210, 210), an$DenDF, tolerance=TOL))
> >>>>>
> >>>>> ########
> >>>>> ## Make case with balanced unordered factors:
> >>>>> cake2 <- cake
> >>>>> cake2$temperature <- factor(cake2$temperature, ordered = FALSE)
> >>>>> # str(cake2)
> >>>>> stopifnot(
> >>>> + !is.ordered(cake2$temperature)
> >>>> + )
> >>>>> m <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), cake2)
> >>>>> (an1 <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.19 5.09 2 42 0.2488 0.7809
> >>>> temperature 2100.30 420.06 5 210 20.5199 <2e-16 ***
> >>>> recipe:temperature 205.98 20.60 10 210 1.0062 0.4393
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> ## Balanced data and only factors: Type I, II, and III should be the
> >>>>> same:
> >>>>> stopifnot(
> >>>> + isTRUE(all.equal(an1, an2, check.attributes=FALSE, tolerance=TOL)),
> >>>> + isTRUE(all.equal(an3, an2, check.attributes=FALSE, tolerance=TOL))
> >>>> + )
> >>>>> ########
> >>>>>
> >>>>> # No intercept:
> >>>>> m <- lmer(angle ~ 0 + recipe * temp + (1|recipe:replicate), cake)
> >>>>> (an <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 21442.9 7147.6 3 42 342.2200 <2e-16 ***
> >>>> temp 1966.7 1966.7 1 222 94.1632 <2e-16 ***
> >>>> recipe:temp 1.7 0.9 2 222 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.48 1.49 3 254.02 0.0714 0.9752
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.48 1.49 3 254.02 0.0714 0.9752
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> if(has_pbkrtest)
> >>>> + (an_KR <- anova(m, ddf="Kenward-Roger"))
> >>>> Type III Analysis of Variance Table with Kenward-Roger's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.48 1.49 3 254.02 0.0714 0.9752
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> recipe 3 21442.9 7147.6 342.2200
> >>>> temp 1 1966.7 1966.7 94.1632
> >>>> recipe:temp 2 1.7 0.9 0.0417
> >>>>> res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_lme4[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>>> stopifnot(isTRUE(res))
> >>>>>
> >>>>> # ML-fit:
> >>>>> m <- lmer(angle ~ recipe * temp + (1|recipe:replicate), cake,
> >>>>> REML=FALSE)
> >>>>> (an <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.99 5.49 2 45 0.2666 0.7672
> >>>> temp 1966.71 1966.71 1 225 95.4357 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 225 0.0423 0.9586
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> if(has_pbkrtest)
> >>>> + assertError(an <- anova(m, ddf="Kenward-Roger")) # KR fits should be
> >>>> REML
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> recipe 2 10.99 5.49 0.2666
> >>>> temp 1 1966.71 1966.71 95.4357
> >>>> recipe:temp 2 1.74 0.87 0.0423
> >>>>> res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_lme4[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>>> stopifnot(isTRUE(res))
> >>>>>
> >>>>> ####################################
> >>>>> ## Using contr.sum:
> >>>>> ####################################
> >>>>>
> >>>>> m <- lmer(angle ~ recipe * temp + (1|recipe:replicate), cake,
> >>>> + contrasts = list('recipe' = "contr.sum"))
> >>>>> (an <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.39 5.20 2 42 0.2488 0.7809
> >>>> temp 1966.71 1966.71 1 222 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.00 2.00 2 254.02 0.0957 0.9088
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 4.00 2.00 2 254.02 0.0957 0.9088
> >>>> temp 1966.71 1966.71 1 222.00 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222.00 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> stopifnot(
> >>>> + isTRUE(all.equal(an2, an3, check.attributes=FALSE, tolerance=TOL))
> >>>> + )
> >>>>> if(has_pbkrtest)
> >>>> + (an_KR <- anova(m, type=1, ddf="Kenward-Roger"))
> >>>> Type I Analysis of Variance Table with Kenward-Roger's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> recipe 10.39 5.20 2 42 0.2488 0.7809
> >>>> temp 1966.71 1966.71 1 222 94.1632 <2e-16 ***
> >>>> recipe:temp 1.74 0.87 2 222 0.0417 0.9592
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> recipe 2 10.39 5.20 0.2488
> >>>> temp 1 1966.71 1966.71 94.1632
> >>>> recipe:temp 2 1.74 0.87 0.0417
> >>>>> res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_lme4[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>>> stopifnot(isTRUE(res))
> >>>>>
> >>>>>
> >>>>> ####################################
> >>>>> ## Example with continuous fixef:
> >>>>> ####################################
> >>>>>
> >>>>> # Example with no fixef:
> >>>>> m <- lmer(Reaction ~ -1 + (Days | Subject), sleepstudy)
> >>>>> # m <- lmer(Reaction ~ 0 + (Days | Subject), sleepstudy) # alternative
> >>>>> stopifnot(length(fixef(m)) == 0L)
> >>>>> (an <- anova(m, type=1))
> >>>> Type I Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> (an_2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> (an_3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> stopifnot(nrow(an) == 0L,
> >>>> + nrow(an_2) == 0L,
> >>>> + nrow(an_3) == 0L)
> >>>>> # anova(m, ddf="lme4") # Bug in lme4 it seems
> >>>>> if(has_pbkrtest) {
> >>>> + (an_KR <- anova(m, ddf="Kenward-Roger"))
> >>>> + stopifnot(
> >>>> + nrow(an_KR) == 0L
> >>>> + )
> >>>> + }
> >>>>>
> >>>>> # Example with intercept only:
> >>>>> m <- lmer(Reaction ~ (Days | Subject), sleepstudy)
> >>>>> # m <- lmer(Reaction ~ 1 + (Days | Subject), sleepstudy) # alternative
> >>>>> stopifnot(length(fixef(m)) == 1L,
> >>>> + names(fixef(m)) == "(Intercept)")
> >>>>> (an <- anova(m))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> (an_2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> (an_3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>>> stopifnot(nrow(an) == 0L,
> >>>> + nrow(an_2) == 0L,
> >>>> + nrow(an_3) == 0L,
> >>>> + nrow(an_lme4) == 0L)
> >>>>> if(has_pbkrtest) {
> >>>> + (an_KR <- anova(m, ddf="Kenward-Roger"))
> >>>> + stopifnot(
> >>>> + nrow(an_KR) == 0L
> >>>> + )
> >>>> + }
> >>>>>
> >>>>> # Example with 1 fixef without intercept:
> >>>>> m <- lmer(Reaction ~ Days - 1 + (Days | Subject), sleepstudy)
> >>>> Warning message:
> >>>> In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
> >>>> Model failed to converge with max|grad| = 0.00416642 (tol = 0.002,
> >>>> component 1)
> >>>>> # m <- lmer(Reaction ~ 0 + Days + (Days | Subject), sleepstudy) #
> >>>> alternative
> >>>>> stopifnot(length(fixef(m)) == 1L,
> >>>> + names(fixef(m)) == "Days")
> >>>>> (an <- anova(m))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 93779 93779 1 16.995 143.19 1.054e-09 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_2 <- anova(m, type=2))
> >>>> Type II Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 93779 93779 1 16.995 143.19 1.054e-09 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_3 <- anova(m, type=3))
> >>>> Type III Analysis of Variance Table with Satterthwaite's method
> >>>> Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
> >>>> Days 93779 93779 1 16.995 143.19 1.054e-09 ***
> >>>> ---
> >>>> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> >>>>> (an_lme4 <- anova(m, ddf="lme4"))
> >>>> Analysis of Variance Table
> >>>> Df Sum Sq Mean Sq F value
> >>>> Days 1 93779 93779 143.19
> >>>>> stopifnot(nrow(an) == 1L,
> >>>> + nrow(an_2) == 1L,
> >>>> + nrow(an_3) == 1L,
> >>>> + nrow(an_lme4) == 1L)
> >>>>> if(has_pbkrtest) {
> >>>> + (an_KR <- anova(m, ddf="Kenward-Roger"))
> >>>> + stopifnot(
> >>>> + nrow(an_KR) == 1L
> >>>> + )
> >>>> + }
> >>>>>
> >>>>> res <- all.equal(an[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> + an_lme4[, c("Sum Sq", "Mean Sq", "F value")],
> >>>> tolerance=TOL)
> >>>>> stopifnot(isTRUE(res))
> >>>>> stopifnot(isTRUE(all.equal(
> >>>> + c(1, 17), unname(unlist(an[, c("NumDF", "DenDF")])), tolerance=TOL
> >>>> + )))
> >>>> Error: isTRUE(all.equal(c(1, 17), unname(unlist(an[, c("NumDF",
> >>>> "DenDF")])), .... is not TRUE
> >>>> Execution halted
> >>>> autopkgtest [04:42:39]: test run-unit-test: -----------------------]
> >>>>
> >>>
> >>>
> >>>
> >>>
> >>>> _______________________________________________
> >>>> R-pkg-team mailing list
> >>>> [email protected]
> >>>> <mailto:[email protected]>
> >>>> https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/r-pkg-team
> >>>> <https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/r-pkg-team>
> >>>
> >>>
> >>> --
> >>> http://fam-tille.de <http://fam-tille.de/>
> >>
> >> --
> >> http://fam-tille.de <http://fam-tille.de/>
>
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