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how to report the results from lmer() in APA-style

4 messages · Liliana Martinez, ONKELINX, Thierry, Peter Dixon

Original
ONKELINX, Thierry
# 
Dear Liliana,

Have at look at https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html. Douglas Bates explaines in that post why you can't find p-values in the summary of lmer().

You could also have a look at RSiteSearch("lmer p-value").

HTH,

Thierry


----------------------------------------------------------------------------
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] Namens Liliana Martinez
Verzonden: maandag 16 februari 2009 15:42
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] how to report the results from lmer() in APA-style

Dear all,

I am trying to apply the lmer function in R 2.8.0. to some linguistic data, but I am at a loss when it comes to reporting the results (see below). The APA recommendations say that effects should be reported as follows:

F (df1, df2) = ... , p. = ... 

The question is, where do I find all these things? So far I have??learned through different sources that df1 and F can be found through using the anova() function (is this??correct?), but where do I find df2 and p ? 
I have even bigger problems when my dependent variable has a binomial distribution, because then the anova() and pvals.fnc() functions cannot be applied.

I wonder as well whether there is a commonly approved way of reporting the output of the 'print (xxx.lmer)' and 'xxx.pvals$fixed' commands? I can see that some of the levels of a factor are significantly different from the baseline, and this is of interests for me, but how??shal I report it? Or should other tests be applied in order to find the difference between the levels? (and, if yes, what tests?)

Any help/ advice/ references??will be greatly appreciated.


Best regards

Liliana

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print (all_v_a_va_vf_vp_vt.lmer , corr = F)
Linear mixed model fit by REML 
Formula: rating ~ verb + angle + verb:angle + verb:type + verb:prec +?????????? verb:fol + (1 | subject) 
???? Data: rating_allbegend_no270 
???? AIC???? BIC logLik deviance REMLdev
??11067 11225?? -5507?????? 10941???? 11015
Random effects:
??Groups???? Name?????????????? Variance Std.Dev.
??subject?? (Intercept) 0.092792 0.30462 
??Residual???????????????????????? 1.691374 1.30053 
Number of obs: 3240, groups: subject, 40
Fixed effects:
???????????????????????????????????????????????????????????? Estimate Std. Error t value
(Intercept)???????????????????????????????????????? 4.51944?????? 0.13102???? 34.49
verbzaobikalia???????????????????????????????? -1.42685?????? 0.15830???? -9.01
verbzaviva???????????????????????????????????????? -2.82315?????? 0.15830?? -17.83
angle180???????????????????????????????????????????? -0.88611?????? 0.09694???? -9.14
angle360???????????????????????????????????????????? -2.84722?????? 0.09694?? -29.37
verbzaobikalia:angle180?????????????? -0.37778?????? 0.13709???? -2.76
verbzaviva:angle180???????????????????????? 1.76944?????? 0.13709???? 12.91
verbzaobikalia:angle360???????????????? 2.24444?????? 0.13709???? 16.37
verbzaviva:angle360???????????????????????? 4.95833?????? 0.13709???? 36.17
verbobikalia:typeround?????????????????? 0.23333?????? 0.12466?????? 1.87
verbzaobikalia:typeround???????????? -0.07407?????? 0.12466???? -0.59
verbzaviva:typeround?????????????????????? 0.35370?????? 0.12466?????? 2.84
verbobikalia:precno_prec???????????? -0.01111?????? 0.09694???? -0.11
verbzaobikalia:precno_prec?????????? 0.20556?????? 0.09694?????? 2.12
verbzaviva:precno_prec???????????????? -0.24722?????? 0.09694???? -2.55
verbobikalia:precsmooth_prec???? -0.19722?????? 0.09694???? -2.03
verbzaobikalia:precsmooth_prec?? 0.12778?????? 0.09694?????? 1.32
verbzaviva:precsmooth_prec???????? -0.15833?????? 0.09694???? -1.63
verbobikalia:folno_fol???????????????? -0.33333?????? 0.09694???? -3.44
verbzaobikalia:folno_fol?????????????? 0.21389?????? 0.09694?????? 2.21
verbzaviva:folno_fol???????????????????? -0.14722?????? 0.09694???? -1.52
verbobikalia:folsmooth_fol???????? -0.26667?????? 0.09694???? -2.75
verbzaobikalia:folsmooth_fol?????? 0.31944?????? 0.09694?????? 3.30
verbzaviva:folsmooth_fol???????????? -0.04167?????? 0.09694???? -0.43
Analysis of Variance Table
???????????????????? Df?? Sum Sq Mean Sq?? F value
verb?????????????? 2?? 131.07???? 65.53?? 38.7458
angle???????????? 2?? 136.09???? 68.05?? 40.2310
verb:angle?? 4 2489.53?? 622.38 367.9741
verb:type???? 3???? 30.62???? 10.21???? 6.0350
verb:prec???? 6???? 27.89?????? 4.65???? 2.7478
verb:fol?????? 6???? 45.62?????? 7.60???? 4.4952
$fixed
???????????????????????????????????????????????????????????? Estimate MCMCmean HPD95lower HPD95upper?? pMCMC Pr(>|t|)
(Intercept)?????????????????????????????????????????? 4.5194???? 4.5198???????? 4.2530???????? 4.7685 0.0001???? 0.0000
verbzaobikalia?????????????????????????????????? -1.4269?? -1.4253?????? -1.7338?????? -1.1122 0.0001???? 0.0000
verbzaviva?????????????????????????????????????????? -2.8231?? -2.8247?????? -3.1252?????? -2.5124 0.0001???? 0.0000
angle180?????????????????????????????????????????????? -0.8861?? -0.8862?????? -1.0768?????? -0.6987 0.0001???? 0.0000
angle360?????????????????????????????????????????????? -2.8472?? -2.8491?????? -3.0388?????? -2.6610 0.0001???? 0.0000
verbzaobikalia:angle180???????????????? -0.3778?? -0.3766?????? -0.6426?????? -0.1051 0.0056???? 0.0059
verbzaviva:angle180?????????????????????????? 1.7694???? 1.7696???????? 1.5117???????? 2.0402 0.0001???? 0.0000
verbzaobikalia:angle360?????????????????? 2.2444???? 2.2465???????? 1.9892???????? 2.5295 0.0001???? 0.0000
verbzaviva:angle360?????????????????????????? 4.9583???? 4.9611???????? 4.7059???????? 5.2427 0.0001???? 0.0000
verbobikalia:typeround???????????????????? 0.2333???? 0.2339?????? -0.0069???????? 0.4895 0.0666???? 0.0613
verbzaobikalia:typeround?????????????? -0.0741?? -0.0757?????? -0.3212???????? 0.1628 0.5384???? 0.5524
verbzaviva:typeround???????????????????????? 0.3537???? 0.3527???????? 0.0980???????? 0.5983 0.0060???? 0.0046
verbobikalia:precno_prec?????????????? -0.0111?? -0.0118?????? -0.2111???????? 0.1717 0.9012???? 0.9088
verbzaobikalia:precno_prec???????????? 0.2056???? 0.2050???????? 0.0145???????? 0.3916 0.0344???? 0.0340
verbzaviva:precno_prec?????????????????? -0.2472?? -0.2456?????? -0.4378?????? -0.0615 0.0136???? 0.0108
verbobikalia:precsmooth_prec?????? -0.1972?? -0.1969?????? -0.3790???????? 0.0009 0.0412???? 0.0420
verbzaobikalia:precsmooth_prec???? 0.1278???? 0.1278?????? -0.0743???????? 0.3078 0.1890???? 0.1875
verbzaviva:precsmooth_prec?????????? -0.1583?? -0.1569?????? -0.3441???????? 0.0336 0.0952???? 0.1025
verbobikalia:folno_fol?????????????????? -0.3333?? -0.3344?????? -0.5240?????? -0.1438 0.0002???? 0.0006
verbzaobikalia:folno_fol???????????????? 0.2139???? 0.2133???????? 0.0254???????? 0.4008 0.0282???? 0.0274
verbzaviva:folno_fol?????????????????????? -0.1472?? -0.1467?????? -0.3379???????? 0.0420 0.1314???? 0.1289
verbobikalia:folsmooth_fol?????????? -0.2667?? -0.2674?????? -0.4645?????? -0.0839 0.0058???? 0.0060
verbzaobikalia:folsmooth_fol???????? 0.3194???? 0.3186???????? 0.1252???????? 0.5074 0.0006???? 0.0010
verbzaviva:folsmooth_fol?????????????? -0.0417?? -0.0412?????? -0.2339???????? 0.1437 0.6828???? 0.6673
$random
?????? Groups?????????????? Name Std.Dev. MCMCmedian MCMCmean HPD95lower HPD95upper
1?? subject (Intercept)???? 0.3046???????? 0.2993???? 0.3027???????? 0.2235???????? 0.3868
2 Residual???????????????????????????? 1.3005???????? 1.3011???? 1.3012???????? 1.2694???????? 1.3329



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