PBIB: A partially balanced incomplete block experiment

Description Format Source Examples

Description

The PBIB data frame has 60 rows and 3 columns.

Format

This data frame contains the following columns:

response

a numeric vector

Treatment

a factor with levels 1 to 15

Block

an ordered factor with levels 1 to 15

Source

Littel, R. C., Milliken, G. A., Stroup, W. W., and Wolfinger, R. D. (1996), SAS System for Mixed Models, SAS Institute (Data Set 1.5.1).

Examples

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str(PBIB)
if (require("lme4", quietly = TRUE, character = TRUE)) {
  options(contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
  ## compare with output 1.7  pp. 24-25
  print(fm1PBIB <- lmer(response ~ Treatment + (1|Block), PBIB))
  print(anova(fm1PBIB))
}

Example output

'data.frame':	60 obs. of  3 variables:
 $ response : num  2.4 2.5 2.6 2 2.7 2.8 2.4 2.7 2.6 2.8 ...
 $ Treatment: Factor w/ 15 levels "1","10","11",..: 7 15 1 5 11 13 14 1 2 1 ...
 $ Block    : Factor w/ 15 levels "1","10","11",..: 1 1 1 1 8 8 8 8 9 9 ...
 - attr(*, "ginfo")=List of 7
  ..$ formula     :Class 'formula'  language response ~ Treatment | Block
  .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
  ..$ order.groups: logi TRUE
  ..$ FUN         :function (x)  
  ..$ outer       : NULL
  ..$ inner       : NULL
  ..$ labels      : list()
  ..$ units       : list()
Linear mixed model fit by REML ['lmerMod']
Formula: response ~ Treatment + (1 | Block)
   Data: PBIB
REML criterion at convergence: 51.9849
Random effects:
 Groups   Name        Std.Dev.
 Block    (Intercept) 0.2157  
 Residual             0.2925  
Number of obs: 60, groups:  Block, 15
Fixed Effects:
(Intercept)   Treatment1  Treatment10  Treatment11  Treatment12  Treatment13  
   2.891311    -0.073789    -0.400249     0.007388     0.161510    -0.273542  
Treatment14  Treatment15   Treatment2   Treatment3   Treatment4   Treatment5  
  -0.400000    -0.032078    -0.485996    -0.436368    -0.107481    -0.086413  
 Treatment6   Treatment7   Treatment8  
   0.019383    -0.102326    -0.109706  
Analysis of Variance Table
          Df Sum Sq Mean Sq F value
Treatment 14  1.834   0.131  1.5312

SASmixed documentation built on May 29, 2017, 12:08 p.m.