Ergometrics experiment with stool types

Description

The ergoStool data frame has 36 rows and 3 columns.

Format

This data frame contains the following columns:

effort

a numeric vector giving the effort (Borg scale) required to arise from a stool

Type

a factor with levels T1, T2, T3, and T4 giving the stool type

Subject

a factor with levels A to I

Details

Devore (2000) cites data from an article in Ergometrics (1993, pp. 519-535) on “The Effects of a Pneumatic Stool and a One-Legged Stool on Lower Limb Joint Load and Muscular Activity.”

Source

Pinheiro, J. C. and Bates, D. M. (2000), Mixed-Effects Models in S and S-PLUS, Springer, New York. (Appendix A.9)

Devore, J. L. (2000), Probability and Statistics for Engineering and the Sciences (5th ed), Duxbury, Boston, MA.

Examples

options(show.signif.stars = FALSE)
str(ergoStool)
print(m1 <- lmer(effort ~ Type + (1|Subject), ergoStool), corr = FALSE)
anova(m1)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(MEMSS)
Loading required package: lme4
Loading required package: Matrix

Attaching package: 'MEMSS'

The following objects are masked from 'package:datasets':

    CO2, Orange, Theoph

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MEMSS/ergoStool.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ergoStool
> ### Title: Ergometrics experiment with stool types
> ### Aliases: ergoStool
> ### Keywords: datasets
> 
> ### ** Examples
> 
> options(show.signif.stars = FALSE)
> str(ergoStool)
'data.frame':	36 obs. of  3 variables:
 $ effort : num  12 15 12 10 10 14 13 12 7 14 ...
 $ Type   : Factor w/ 4 levels "T1","T2","T3",..: 1 2 3 4 1 2 3 4 1 2 ...
 $ Subject: Factor w/ 9 levels "A","B","C","D",..: 1 1 1 1 2 2 2 2 3 3 ...
> print(m1 <- lmer(effort ~ Type + (1|Subject), ergoStool), corr = FALSE)
Linear mixed model fit by REML ['lmerMod']
Formula: effort ~ Type + (1 | Subject)
   Data: ergoStool
REML criterion at convergence: 121.1308
Random effects:
 Groups   Name        Std.Dev.
 Subject  (Intercept) 1.332   
 Residual             1.100   
Number of obs: 36, groups:  Subject, 9
Fixed Effects:
(Intercept)       TypeT2       TypeT3       TypeT4  
     8.5556       3.8889       2.2222       0.6667  
> anova(m1)
Analysis of Variance Table
     Df Sum Sq Mean Sq F value
Type  3 81.194  27.065  22.356
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>