This analysis reproduces the predicted cell frequencies for Bartlett’s data by using a log-linear model of no three-variable
interaction (Bishop, Fienberg, and Holland, 1975, p. 89). Cuttings of two different lengths (Length
=short or long) are planted at one of two time points (Time
=now or spring), and their survival status (Status
=dead or alive) is recorded.
As in the text, the variable levels are simply labeled 1 and 2. The following statements produce Output 32.4.1 through Output 32.4.3:
data bartlett; input Length Time Status wt @@; datalines; 1 1 1 156 1 1 2 84 1 2 1 84 1 2 2 156 2 1 1 107 2 1 2 133 2 2 1 31 2 2 2 209 ;
title 'Bartlett''s Data'; proc catmod data=bartlett; weight wt; model Length*Time*Status=_response_ / noparm pred=freq; loglin Length|Time|Status @ 2; title2 'Model with No 3-Variable Interaction'; quit;
Output 32.4.1: Analysis of Bartlett's Data: Log-Linear Model
Bartlett's Data |
Model with No 3-Variable Interaction |
Data Summary | |||
---|---|---|---|
Response | Length*Time*Status | Response Levels | 8 |
Weight Variable | wt | Populations | 1 |
Data Set | BARTLETT | Total Frequency | 960 |
Frequency Missing | 0 | Observations | 8 |
Population Profiles | |
---|---|
Sample | Sample Size |
1 | 960 |
Response Profiles | |||
---|---|---|---|
Response | Length | Time | Status |
1 | 1 | 1 | 1 |
2 | 1 | 1 | 2 |
3 | 1 | 2 | 1 |
4 | 1 | 2 | 2 |
5 | 2 | 1 | 1 |
6 | 2 | 1 | 2 |
7 | 2 | 2 | 1 |
8 | 2 | 2 | 2 |
Maximum Likelihood Analysis |
---|
Maximum likelihood computations converged. |
Maximum Likelihood Analysis of Variance | |||
---|---|---|---|
Source | DF | Chi-Square | Pr > ChiSq |
Length | 1 | 2.64 | 0.1041 |
Time | 1 | 5.25 | 0.0220 |
Length*Time | 1 | 5.25 | 0.0220 |
Status | 1 | 48.94 | <.0001 |
Length*Status | 1 | 48.94 | <.0001 |
Time*Status | 1 | 95.01 | <.0001 |
Likelihood Ratio | 1 | 2.29 | 0.1299 |
The analysis of variance table shows that the model fits since the likelihood ratio test for the three-variable interaction is nonsignificant. All of the two-variable interactions, however, are significant; this shows that there is mutual dependence among all three variables.
The predicted values table (Output 32.4.2) displays observed and predicted values for the generalized logits.
Output 32.4.2: Response Function Predicted Values
Maximum Likelihood Predicted Values for Response Functions | |||||
---|---|---|---|---|---|
Function Number |
Observed | Predicted | Residual | ||
Function | Standard Error |
Function | Standard Error |
||
1 | -0.29248 | 0.105806 | -0.23565 | 0.098486 | -0.05683 |
2 | -0.91152 | 0.129188 | -0.94942 | 0.129948 | 0.037901 |
3 | -0.91152 | 0.129188 | -0.94942 | 0.129948 | 0.037901 |
4 | -0.29248 | 0.105806 | -0.23565 | 0.098486 | -0.05683 |
5 | -0.66951 | 0.118872 | -0.69362 | 0.120172 | 0.024113 |
6 | -0.45199 | 0.110921 | -0.3897 | 0.102267 | -0.06229 |
7 | -1.90835 | 0.192465 | -1.73146 | 0.142969 | -0.17688 |
The predicted frequencies table (Output 32.4.3) displays observed and predicted cell frequencies, their standard errors, and residuals.
Output 32.4.3: Predicted Frequencies
Maximum Likelihood Predicted Values for Frequencies | |||||||
---|---|---|---|---|---|---|---|
Length | Time | Status | Observed | Predicted | Residual | ||
Frequency | Standard Error |
Frequency | Standard Error |
||||
1 | 1 | 1 | 156 | 11.43022 | 161.0961 | 11.07379 | -5.09614 |
1 | 1 | 2 | 84 | 8.754999 | 78.90386 | 7.808613 | 5.096139 |
1 | 2 | 1 | 84 | 8.754999 | 78.90386 | 7.808613 | 5.096139 |
1 | 2 | 2 | 156 | 11.43022 | 161.0961 | 11.07379 | -5.09614 |
2 | 1 | 1 | 107 | 9.750588 | 101.9039 | 8.924304 | 5.096139 |
2 | 1 | 2 | 133 | 10.70392 | 138.0961 | 10.33434 | -5.09614 |
2 | 2 | 1 | 31 | 5.47713 | 36.09614 | 4.826315 | -5.09614 |
2 | 2 | 2 | 209 | 12.78667 | 203.9039 | 12.21285 | 5.09614 |