Description Usage Format Source References Examples

One company of soldiers in each of 10 platoons was assigned to a Pygmalion treatment group, with remaining companies in the platoon assigned to a control group. Leaders of the Pygmalion platoons were told their soldiers had done particularly well on a battery of tests which were, in fact, non-existent. In this randomised block experiment, platoons are experimental units, companies are blocks, and average Practical Specialty test score for soldiers in a platoon is the response. The researchers wished to see if the platoon response was affected by the artificially-induced expectations of the platoon leader.

1 |

A data frame with 29 observations on the following 3 variables.

`Company`

a factor indicating company identification, with levels

`"C1"`

,`"C2"`

, ...,`"C10"`

`Treat`

a factor indicating treatment with two levels,

`"Pygmalion"`

and`"Control"`

`Score`

average score on practical specialty test of all soldiers in the platoon

Ramsey, F.L. and Schafer, D.W. (2002). *The Statistical Sleuth: A
Course in Methods of Data Analysis (2nd ed)*, Duxbury.

Eden, D. (1990). Pygmalion Without Interpersonal Contrast Effects:
Whole Groups Gain from Raising Manager Expectations, *Journal of
Applied Psychology* **75**(4): 395–398.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
str(case1302)
# two-way model with interactions
fitfull <- aov(Score ~ Company*Treat, case1302)
# No problems are indicated by residual plot
plot(fitfull)
# Interaction terms are not statistically significant
anova(fitfull)
# Additive model, with "treatment contrast" for treatment:
fitadditive <- aov(Score ~ Company + Treat, case1302)
# Interpret treatment effect as coefficient of Treat
anova(fitadditive)
``` |

```
'data.frame': 29 obs. of 3 variables:
$ Company: Factor w/ 10 levels "C1","C2","C3",..: 1 1 1 2 2 2 3 3 4 4 ...
$ Treat : Factor w/ 2 levels "Pygmalion","Control": 1 2 2 1 2 2 1 2 1 2 ...
$ Score : num 80 63.2 69.2 83.9 63.1 ...
Warning messages:
1: not plotting observations with leverage one:
1, 4, 7, 8, 9, 12, 15, 18, 21, 24, 27
2: not plotting observations with leverage one:
1, 4, 7, 8, 9, 12, 15, 18, 21, 24, 27
Analysis of Variance Table
Response: Score
Df Sum Sq Mean Sq F value Pr(>F)
Company 9 670.98 74.55 1.4367 0.29902
Treat 1 338.88 338.88 6.5304 0.03092 *
Company:Treat 9 311.46 34.61 0.6669 0.72212
Residuals 9 467.04 51.89
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Analysis of Variance Table
Response: Score
Df Sum Sq Mean Sq F value Pr(>F)
Company 9 670.98 74.55 1.7238 0.15556
Treat 1 338.88 338.88 7.8354 0.01186 *
Residuals 18 778.50 43.25
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
```

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