Stat Computing > SPSS > Textbook Examples > Regression with Graphics, by Hamilton

SPSS Textbook Examples
Regression with Graphics by Lawrence Hamilton
Chapter 7: Logit regression

Limitations of linear regression

Page 218 Figure 7.1  Linear regression of a dichotomous Y variable (0 = open schools, 1 = close schools) on a measurement X variable (years lived in town).

GET FILE 'd:\apps\rwgdata\toxic.sav'.

IGRAPH
 /X1 = VAR(lived)
 /Y = VAR(close) type=scale
 /FITLINE METHOD = REGRESSION LINEAR LINE = TOTAL
 /SCATTER.

Interactive Graph

Page 219 Figure 7.2  Boxplots and oneway scatterplots of years lived in town, for respondents favoring closed and open schools.

compute const=.01.
execute.

EXAMINE  VARIABLES=lived BY close
 /PLOT=BOXPLOT
 /STATISTICS=NONE.

Explore

Total Sample

years lived in Williamstown

schools should close

years lived in Williamstown

Page 222 Figure 7.4  Logit regression of school-closing opinion on years lived in town, also showing linear regression line.

NOTE:  SPSS will not allow you to graph two regression lines and the data points on the same graph.

Estimation

Page 224 Table 7.1  Logit regression of school-closing opinion on years lived in town.

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

Hypothesis Tests and Confidence Intervals

Page 226 Table 7.2  Logit regression of school-closing opinion on years lived in town, education, contamination, and HSC meetings.

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived educ contam hsc.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

Page 227 Table 7.3  Logit regression of school-closing opinion on seven background variables.

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived educ contam hsc female kids nodad
  /PRINT=ITER(1) SUMMARY.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

Page 228 Table 7.4  Reduced model with male/nonparent interaction term.

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived educ contam hsc nodad.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

  Interpretation

Page 232 Figure 7.5  Conditional effects of years lived in town, at proclosing (top), average, and anticlosing levels of other X variables.

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived educ contam hsc nodad.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

SORT CASES BY
  lived (A).

compute lhat1 = 3.17-.04*lived.
compute phat1 = 1/(1+exp(-lhat1)).
compute lhat2 = .387-.04*(lived).
compute phat2 = 1/(1+exp(-lhat2)).
compute lhat3 = -2.14-.04*(lived).
compute phat3 = 1/(1+exp(-lhat3)).
execute.

GRAPH
  /SCATTERPLOT(OVERLAY)=lived lived lived  WITH phat1 phat2 phat3 (PAIR).

Graph

Page 232 Figure 7.6  Conditional effects of contamination, at proclosing, average, and anticlosing levels of other X variables.

NOTE:  This graph does not look exactly like the one in the text because of scaling issues on the X-axis.

SORT CASES BY contam (A).
compute lhat4 = 3.22+1.3*(contam).
compute phat4 = 1/(1+exp(-lhat4)).
compute lhat5 = -.7681+1.3*(contam).
compute phat5 = 1/(1+exp(-lhat5)).
compute lhat6 = -6.79+1.3*(contam).
compute phat6 = 1/(1+exp(-lhat6)).
execute.

SORT CASES BY
  contam (A).

GRAPH
  /LINE(MULTIPLE)= VALUE( phat4 phat5 phat6 ) BY contam.

Graph

Diagnostic graphs

Page 239 Figure 7.7  Poorness-of-fit statistic delta-chi-square(P) versus predicted probability of favoring closed schools; X patterns 131 and 3 are poorly fit (high delta-chi-square(P) values).

LOGISTIC REGRESSION VAR=close
  /METHOD=ENTER lived educ contam hsc nodad
  /SAVE PRED COOK LEVER ZRESID DEV.

Logistic Regression

Block 0: Beginning Block

Block 1: Method = Enter

compute deltap=(zre_1)**2/(1-lev_1).
execute.

GRAPH
  /SCATTERPLOT(BIVAR)=pre_1 WITH deltap.

Graph

Page 240 Figure 7.8  Poorness-of-fit statistic delta-chi-square(D) versus predicted probability of favoring closed schools; X patterns 131, 3, 27, 62, 115 are poorly fit (high delta-chi-square(D) values).

compute deltad=(dev_1)**2/(1-lev_1).
execute.

GRAPH
  /SCATTERPLOT(BIVAR)=pre_1 WITH deltad.

Graph

Page 241 Figure 7.9  Influence statistic delta-B versus predicted probability of favoring closed schools; patterns 131, 3, 115, 44, and 94 are most influential (high delta-B values).

NOTE:  Delta-B is the Cook's D statistic.

GRAPH
  /SCATTERPLOT(BIVAR)=pre_1 WITH coo_1.

Graph

Page 242 Figure 7.10  Delta-chi-square(D) versus P-hat with symbols proportional to delta-B; large, high circles indicate influential, poorly fit X patterns.

NOTE:  We do not know how to make the bubbles (symbols) proportional.

GRAPH
  /SCATTERPLOT(BIVAR)=pre_1 WITH deltad.

Graph

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