Displaying 20 results from an estimated 4000 matches similar to: "How to extract coefficients from sequential (type 1), ANOVAs using lmer and lme"
2017 Nov 29
0
How to extract coefficients from sequential (type 1), ANOVAs using lmer and lme
(This time with the r-help in the recipients...)
Be careful when mixing lme4 and lmerTest together -- lmerTest extends
and changes the behavior of various lme4 functions.
>From the help page for lme4-anova (?lme4::anova.merMod)
> ?anova?: returns the sequential decomposition of the contributions
> of fixed-effects terms or, for multiple arguments, model
>
2017 Nov 27
0
How to extract coefficients from sequential (type 1) ANOVAs using lmer and lme
I wantto run sequential ANOVAs (i.e. type I sums of squares), and trying to getresults including ANOVA tables and associated coefficients for predictive variables(I am using the R 3.4.2 version). I think ANOVA tables look right, but believecoefficients are wrong. Specifically, it looks like that the coefficients arefrom ANOVA with ?marginal? (type III sums of squares). I have tried both lme
2016 Jul 18
0
summary() dispatch puzzle
>>>>> Ben Bolker <bbolker at gmail.com>
>>>>> on Fri, 15 Jul 2016 16:45:50 -0400 writes:
> I'm sorry I haven't boiled this down to a more-minimal example yet,
> but ...
> I'm working on an S3 method (tidy.merMod, in the 'broom' package). It
> normally handles 'merMod' objects from the lme4 package,
2016 Jul 15
2
summary() dispatch puzzle
I'm sorry I haven't boiled this down to a more-minimal example yet,
but ...
I'm working on an S3 method (tidy.merMod, in the 'broom' package). It
normally handles 'merMod' objects from the lme4 package, but I'm trying
to make it handle 'merModLmerTest' objects from the lmerTest package too.
The merModLmerTest class inherits (as an S4) class from the
2013 Sep 13
2
R CMD check fails in R-devel r63910
Hi,
The R CMD check is successful in R 3.0.1 but fails to install package
lmerTest under R-devel r63910,
Here is what I get:
** preparing package for lazy loading
Error in reconcilePropertiesAndPrototype(name, slots, prototype,
superClasses, :
no definition was found for superclass "merMod" in the specification of
class "merModLmerTest"
In DESCRIPTION file I have:
2017 Oct 11
0
Converting SAS Code
I have no problem setting up my mixed model, or performing anova or lsmeans
on my model?s outputs. However, performing lsd mean separation is giving me
fits.
So I do not have a problem when using two-way anova model. When using the
code:
fit.yield.add <- lm(data = ryzup, Yield ~ Rep + Nitrogen + Treatment)
LSD.test(fit.yield.add, trt = "Nitrogen", alpha = 0.1, console = TRUE)
2018 Jan 05
0
Calculating the correlations of nested random effects in lme4
I postulate the following model
AC <- glmer(Accuracy ~ RT*Group + (1+RT|Group:subject) +
(1+RT|Group:Trial), data = da, family = binomial, verbose = T)
Here I predict Accuracy from RT, Group (which has values 0 or 1) and the
interaction of Group and RT (those are the fixed effects). I also estimate
the random effects for both intercepts and slopes for subjects and
different trials.
2013 Oct 12
1
lmerTest
Hi,
I'm trying to user lmer function from lmerTest package because, if I
understood correectly, it allows to make better inference than lmer method
from lme4 package. However, whatever I do I keep getting this error:
Error in lme4::lFormula(formula = mark ~ ssCount + sTime+ : rank of X =
1660 < ncol(X) = 1895
any ideas what could be a problem?
thanks,
Srecko
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2017 Dec 08
1
lmerTest Issues
Hello all,
Everything was working very well. Now when I try to load lmerTest using:
library("lmerTest"), I get this error:
Error: package or namespace load failed for ?lmerTest? in
loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck =
vI[[j]]):
there is no package called ?purrr?
Nothing I've done has worked. I have uninstalled both R and R studio. I've
2011 Jul 28
1
Help Non-sequential ANOVAs
Hello,
I have data
on the maturity of two morphs of fish. I want to test whether their maturity is
evolving differently or not on a temporal scale (month). The maturity variable (independent
variable) is continuous and the morph and month variables (dependant variables)
are categorical. Because the data show variance heterogeneity, I modeled it
with the function gls:
kg1 =
2013 Nov 16
1
repeated-measures multiple regression/ANCOVA/MANCOVA
Dear List,
I am trying to analyze a dataset where I have 1 continuous
between-item variable (C), and 2 factorial within-item variables (3-
and 2-level: F3, F2). I'm interested in whether slope of C is
different from 0 at different combinations of F3 and F2, and whether
it varies between these combinations.
And unfortunately I need a decent anova-like table with p-values. The
reason is that
2008 Sep 14
3
Nonlinear regression question&In-Reply-To=6rya22mljx.fsf@franz.stat.wisc.edu
I was unable to open this file Bill Venables' excellent "Exegeses on
Linear Models" posted at
http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.ps.gz I'd be very
interested in reading it?
Thanks
Esther Meenken
Biometrician
Crop & Food Research
Private Bag 4704
Christchurch
TEL: (03) 325 9639
FAX: (03) 325 2074
EMAIL:MeenkenE at crop.cri.nz
Visit our website at
2017 Sep 30
4
Converting SAS Code
On 9/29/2017 3:37 PM, Rolf Turner wrote:
> On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote:
>
> <SNIP>
>
>>
>> The conceptual paradigm for R is only marginally commensurate with
>> that of
>> standard statistical software.
>> You must immerse yourself in R to become proficient.
>
> Fortune nomination.
For newer list members wondering what
2011 Jan 21
0
Marginality rule between powers and interaction terms in lm()
Dear all,
I have a model with simple terms, quadratic effects, and interactions.
I am wondering what to do when a variable is involved in a significant
interaction and in a non-significant quadratic effect. Here is an
example
d = data.frame(a=runif(20), b=runif(20))
d$y = d$a + d$b^2
So I create both an simple effect of a and a quadratic effect of b.
m = lm(y ~ a + b + I(a^2) + I(b^2) +
2002 Nov 13
0
Welch versus Satterthwaith (PR#2111)
>>>>> "TL" == Thomas Lumley <tlumley@u.washington.edu>
>>>>> on Sun, 6 Oct 2002 09:19:27 -0700 (PDT) writes:
TL> On Sat, 5 Oct 2002 roxburg@kih.net wrote:
>> This is not a bug report but didn't see another way to
>> ask a question.
TL> Well, you could try the r-help or r-devel mailing lists
>> For
2013 Jan 09
0
[solved] t-test behavior given that the null hypothesis is true
Hi Ted,
yes this was the problem. Thank you very much.
best
idaios
On Wed, Jan 9, 2013 at 4:51 PM, Ted Harding <Ted.Harding@wlandres.net>wrote:
> Ah! You have aqssigned a parameter "equal.var=TRUE", and "equal.var"
> is not a listed paramater for t.test() -- see ?t.test :
>
> t.test(x, y = NULL,
> alternative = c("two.sided",
2008 May 25
1
marginality principle / selecting the right type of SS for an interaction hypothesis
Hello,
I have a problem with selecting the right type of sums of squares for
an ANCOVA for my specific experimental data and hypotheses. I do have
a basic understanding of the differences between Type-I, II, and III
SSs, have read about the principle of marginality, and read Venable's
"Exegeses on Linear Models"
(http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf). I am pretty new to
2017 Sep 30
1
Converting SAS Code
> On 30 Sep 2017, at 14:22 , Robert Baer <rbaer at atsu.edu> wrote:
>
>
>
> On 9/29/2017 3:37 PM, Rolf Turner wrote:
>> On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote:
>>
>> <SNIP>
>>
>>>
>>> The conceptual paradigm for R is only marginally commensurate with
>>> that of
>>> standard statistical
2005 Oct 25
1
Confidence Intervals for Mixed Effects
I'm fairly new to R and am wondering if anybody knows of R code to
calculate confidence intervals for parameters (fixed effects and variance
components) from mixed effects models based on Sattherthwaite's method?
I'm also interested in Satterthwaite-based confidence intervals for linear
combinations (mostly sums) of various variance components.
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2017 Dec 26
1
identifying convergence or non-convergence of mixed-effects regression model in lme4 from model output
Hi R community!
I've fitted three mixed-effects regression models to a thousand
bootstrap samples (case-resampling regression) using the lme4 package in
a custom-built for-loop. The only output I saved were the inferential
statistics for my fixed and random effects. I did not save any output
related to the performance to the machine learning algorithm used to fit
the models (REML=FALSE).