pvals.fnc: Compute p-values and MCMC confidence intervals for mixed...

In languageR: Analyzing Linguistic Data: A Practical Introduction to Statistics

Description

This function used to calculate p-values and HPD intervals for the parameters of models fitted with lmer.

As MCMC is no longer supported by lme4, this function is now obsolete and does no longer produce any output, other than a warning.

See the lme4 function pvalues() for alternatives.

Usage

pvals.fnc(object, ...)

Arguments

object	a LMM or GLMM model object of class lmerMod
...	Optional arguments that can be passed down.

Value

A warning.

Author(s)

R. H. Baayen

See Also

pvalues

Examples

  ## Not run: 
  data(primingHeid) 
  library(lme4)

  # remove extreme outliers
  primingHeid = primingHeid[primingHeid$RT < 7.1,]

  # fit mixed-effects model

  # we will stay as close to the older optimizer of lme4 as possible -
  # this requires the optimx package and using the control option of lmer()

  require(optimx)
  require(lmerTest)

  primingHeid.lmer = lmer(RT ~ RTtoPrime * ResponseToPrime + 
    Condition + (1|Subject) + (1|Word), data = primingHeid,
    control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")))
  summary(primingHeid.lmer)
  anova(primingHeid.lmer)
  
## End(Not run)

Example output

Loading required package: Matrix
Loading required package: optimx
Loading required package: lmerTest

Attaching package: 'lmerTest'

The following object is masked from 'package:lme4':

    lmer

The following object is masked from 'package:stats':

    step

Linear mixed model fit by REML t-tests use Satterthwaite approximations to
  degrees of freedom [lmerMod]
Formula: RT ~ RTtoPrime * ResponseToPrime + Condition + (1 | Subject) +  
    (1 | Word)
   Data: primingHeid
Control: lmerControl(optimizer = "optimx", optCtrl = list(method = "nlminb"))

REML criterion at convergence: -411.2

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-2.4572 -0.6834 -0.1277  0.6066  3.4185 

Random effects:
 Groups   Name        Variance Std.Dev.
 Word     (Intercept) 0.001252 0.03538 
 Subject  (Intercept) 0.022216 0.14905 
 Residual             0.029575 0.17198 
Number of obs: 787, groups:  Word, 40; Subject, 26

Fixed effects:
                                    Estimate Std. Error        df t value
(Intercept)                          5.27073    0.20767 732.90000  25.380
RTtoPrime                            0.19871    0.03145 732.90000   6.318
ResponseToPrimeincorrect             1.63316    0.36722 745.10000   4.447
Conditionheid                       -0.03876    0.01393 752.40000  -2.782
RTtoPrime:ResponseToPrimeincorrect  -0.22877    0.05511 749.70000  -4.151
                                   Pr(>|t|)    
(Intercept)                         < 2e-16 ***
RTtoPrime                          4.59e-10 ***
ResponseToPrimeincorrect           1.00e-05 ***
Conditionheid                       0.00553 ** 
RTtoPrime:ResponseToPrimeincorrect 3.69e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
            (Intr) RTtPrm RspnTP Cndtnh
RTtoPrime   -0.989                     
RspnsTPrmnc -0.489  0.493              
Conditionhd  0.401 -0.431 -0.169       
RTtPrm:RsTP  0.489 -0.493 -0.999  0.160
Analysis of Variance Table of type III  with  Satterthwaite 
approximation for degrees of freedom
                           Sum Sq Mean Sq NumDF  DenDF F.value    Pr(>F)    
RTtoPrime                 0.23526 0.23526     1 770.21  7.9544   0.00492 ** 
ResponseToPrime           0.58497 0.58497     1 745.15 19.7789 1.002e-05 ***
Condition                 0.22897 0.22897     1 752.42  7.7419   0.00553 ** 
RTtoPrime:ResponseToPrime 0.50957 0.50957     1 749.67 17.2295 3.693e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

languageR documentation built on May 2, 2019, 10:02 a.m.