# PBIB: A partially balanced incomplete block experiment In SASmixed: Data sets from "SAS System for Mixed Models"

## 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

 ```1 2 3 4 5 6 7``` ```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.