* Example 1. * Table 1, page 264. DATA LIST LIST / subject cond1 cond2 cond3. BEGIN DATA. 1 100 90 130 2 90 100 100 3 110 110 109 4 100 90 109 5 100 100 130 END DATA.

GLM cond1 cond2 cond3 /WSFACTOR = conditn 3.

Tests of Within-Subjects Effects Measure: MEASURE_1The

GLMcommand produces 3 of the results shown on Table 1 on page 264.

1. Anova with uncorrected df: F(2,8) = 4.73, p = 0.044, shown in red in the table immediately below.

2. Anova with Huynh-Feldt corrected df, F(1.59, 6.36) = 4.73, shown in pink in the table immediately below

3. MANOVA (Wilks’s Lambda), F(2,3) = 2.40, p=0.238, shown in blue in the second table below.

Source | Type III Sum of Squares | df | Mean Square | F | Sig. | |
---|---|---|---|---|---|---|

CONDITN | Sphericity Assumed | 928.533 | 2 | 464.267 | 4.725 | .044 |

Greenhouse-Geisser | 928.533 | 1.269 | 731.910 | 4.725 | .077 | |

Huynh-Feldt | 928.533 | 1.590 | 583.935 | 4.725 | .060 | |

Lower-bound | 928.533 | 1.000 | 928.533 | 4.725 | .095 | |

Error(CONDITN) | Sphericity Assumed | 786.133 | 8 | 98.267 | ||

Greenhouse-Geisser | 786.133 | 5.075 | 154.916 | |||

Huynh-Feldt | 786.133 | 6.361 | 123.596 | |||

Lower-bound | 786.133 | 4.000 | 196.533 |

Multivariate Tests(b)

Effect | Value | F | Hypothesis df | Error df | Sig. | |
---|---|---|---|---|---|---|

CONDUIT | Pillai’s Trace | .615 | 2.401(a) | 2.000 | 3.000 | .238 |

Wilks’ Lambda | .385 | 2.401(a) | 2.000 | 3.000 | .238 | |

Hotelling’s Trace | 1.601 | 2.401(a) | 2.000 | 3.000 | .238 | |

Roy’s Largest Root | 1.601 | 2.401(a) | 2.000 | 3.000 | .238 | |

a Exact statistic | ||||||

b Design: Intercept Within Subjects Design: CONDITN |

* Example 2. * Table 3, page 268. DATA LIST LIST / subject c1t1 c1t2 c1t3 c2t1 c2t2 c2t3 c3t1 c3t2 c3t3. BEGIN DATA. 1 8 9 8 8 9 7 10 9 10 2 9 10 9 10 9 13 8 9 9 3 8 7 7 12 7 9 10 9 7 4 6 8 9 8 10 10 12 9 10 5 7 6 7 11 12 8 8 11 9 END DATA.

GLM c1t1 c1t2 c1t3 c2t1 c2t2 c2t3 c3t1 c3t2 c3t3 /WSFACTOR = cond 3 trial 3.

The

GLMcommand produces two of the results shown on Table 3 on page 268.

1. Anova with Huynh-Feldt corrected df, F(2,8) = 4.02, shown in pink in the table immediately below

2. MANOVA (Wilks’s Lambda), F(2,3) = 3.30, p=0.175, shown in blue in the second table below.

Source | Type III Sum of Squares | df | Mean Square | F | Sig. | |
---|---|---|---|---|---|---|

COND | Sphericity Assumed | 24.844 | 2 | 12.422 | 4.022 | .062 |

Greenhouse-Geisser | 24.844 | 1.976 | 12.570 | 4.022 | .063 | |

Huynh-Feldt | 24.844 | 2.000 | 12.422 | 4.022 | .062 | |

Lower-bound | 24.844 | 1.000 | 24.844 | 4.022 | .115 | |

Error(COND) | Sphericity Assumed | 24.711 | 8 | 3.089 | ||

Greenhouse-Geisser | 24.711 | 7.906 | 3.126 | |||

Huynh-Feldt | 24.711 | 8.000 | 3.089 | |||

Lower-bound | 24.711 | 4.000 | 6.178 | |||

TRIAL | Sphericity Assumed | .311 | 2 | .156 | .063 | .940 |

Greenhouse-Geisser | .311 | 1.783 | .174 | .063 | .924 | |

Huynh-Feldt | .311 | 2.000 | .156 | .063 | .940 | |

Lower-bound | .311 | 1.000 | .311 | .063 | .815 | |

Error(TRIAL) | Sphericity Assumed | 19.911 | 8 | 2.489 | ||

Greenhouse-Geisser | 19.911 | 7.134 | 2.791 | |||

Huynh-Feldt | 19.911 | 8.000 | 2.489 | |||

Lower-bound | 19.911 | 4.000 | 4.978 | |||

COND * TRIAL | Sphericity Assumed | 1.689 | 4 | .422 | .191 | .940 |

Greenhouse-Geisser | 1.689 | 2.601 | .649 | .191 | .878 | |

Huynh-Feldt | 1.689 | 4.000 | .422 | .191 | .940 | |

Lower-bound | 1.689 | 1.000 | 1.689 | .191 | .685 | |

Error(COND*TRIAL) | Sphericity Assumed | 35.422 | 16 | 2.214 | ||

Greenhouse-Geisser | 35.422 | 10.402 | 3.405 | |||

Huynh-Feldt | 35.422 | 16.000 | 2.214 | |||

Lower-bound | 35.422 | 4.000 | 8.856 |

**Multivariate Tests(b)**

Effect | Value | F | Hypothesis df | Error df | Sig. | |
---|---|---|---|---|---|---|

COND | Pillai’s Trace | .688 | 3.301(a) | 2.000 | 3.000 | .175 |

Wilks’ Lambda | .312 | 3.301(a) | 2.000 | 3.000 | .175 | |

Hotelling’s Trace | 2.201 | 3.301(a) | 2.000 | 3.000 | .175 | |

Roy’s Largest Root | 2.201 | 3.301(a) | 2.000 | 3.000 | .175 | |

TRIAL | Pillai’s Trace | .028 | .043(a) | 2.000 | 3.000 | .959 |

Wilks’ Lambda | .972 | .043(a) | 2.000 | 3.000 | .959 | |

Hotelling’s Trace | .028 | .043(a) | 2.000 | 3.000 | .959 | |

Roy’s Largest Root | .028 | .043(a) | 2.000 | 3.000 | .959 | |

COND * TRIAL | Pillai’s Trace | .348 | .133(a) | 4.000 | 1.000 | .948 |

Wilks’ Lambda | .652 | .133(a) | 4.000 | 1.000 | .948 | |

Hotelling’s Trace | .533 | .133(a) | 4.000 | 1.000 | .948 | |

Roy’s Largest Root | .533 | .133(a) | 4.000 | 1.000 | .948 | |

a Exact statistic | ||||||

b Design: Intercept Within Subjects Design: COND+TRIAL+COND*TRIAL |

* Example 3. * Table 4, page 269. DATA LIST LIST / subject cond1 cond2 cond3 . BEGIN DATA. 1 8.333 8.000 9.667 2 9.333 10.667 8.667 3 7.333 9.333 8.667 4 7.667 9.333 10.333 5 6.667 10.333 9.333 END DATA.

GLM cond1 cond2 cond3 /WSFACTOR cond 3.

The

GLMcommand produces two of the results shown on Table 4 on page 269.

1. Anova with Huynh-Feldt corrected df, F(2,8) = 4.02, shown in pink in the table immediately below

2. MANOVA (Wilks’s Lambda), F(2,3) = 3.31, p=0.174, shown in blue in the second table below.

Tests of Within-Subjects EffectsMeasure: MEASURE_1

Source | Type III Sum of Squares | df | Mean Square | F | Sig. | |
---|---|---|---|---|---|---|

COND | Sphericity Assumed | 8.282 | 2 | 4.141 | 4.023 | .062 |

Greenhouse-Geisser | 8.282 | 1.976 | 4.191 | 4.023 | .063 | |

Huynh-Feldt | 8.282 | 2.000 | 4.141 | 4.023 | .062 | |

Lower-bound | 8.282 | 1.000 | 8.282 | 4.023 | .115 | |

Error(COND) | Sphericity Assumed | 8.234 | 8 | 1.029 | ||

Greenhouse-Geisser | 8.234 | 7.905 | 1.042 | |||

Huynh-Feldt | 8.234 | 8.000 | 1.029 | |||

Lower-bound | 8.234 | 4.000 | 2.058 |

Effect | Value | F | Hypothesis df | Error df | Sig. | |
---|---|---|---|---|---|---|

COND | Pillai’s Trace | .688 | 3.304(a) | 2.000 | 3.000 | .174 |

Wilks’ Lambda | .312 | 3.304(a) | 2.000 | 3.000 | .174 | |

Hotelling’s Trace | 2.203 | 3.304(a) | 2.000 | 3.000 | .174 | |

Roy’s Largest Root | 2.203 | 3.304(a) | 2.000 | 3.000 | .174 | |

a Exact statistic | ||||||

b Design: Intercept Within Subjects Design: COND |