[R-pkg-team] Bug#921938: lme4 breaks r-cran-lmertest autopkgtest
Andreas Tille
tille at debian.org
Sun Feb 10 15:07:12 GMT 2019
Hi again,
may be you get all the relevant information directly from CRAN:
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 <perbb at dtu.dk>
>
> 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: debian-ci at lists.debian.org
> > User: debian-ci at lists.debian.org
> > 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
> >
> > Paul
> >
> > [1] https://qa.debian.org/excuses.php?package=lme4
> >
> > 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
> > R-pkg-team at alioth-lists.debian.net
> > https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/r-pkg-team
>
>
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