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Presenting the Results of a Contingency Table Analysis

Presenting the Results of a Contingency Table Analysis. Verdict x Defendant Physical Attractiveness.

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Presenting the Results of a Contingency Table Analysis

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  1. Presenting the Results of a Contingency Table Analysis

  2. Verdict x Defendant Physical Attractiveness • Mock jurors were significantly more likely to find the defendant guilty when he was unattractive (75.7%) than when he was attractive (65.0%), 2(1, N = 145) = 6.229, p = .013,  = .207, odds ratio = 2.45, 95% CI [1.20, 4.99]. • Please note that with significant results one should emphasize the direction of effect.

  3. Nonsignificant Results • One should NOT mention direction of effect, unless having tested directional hypotheses.

  4. Direction x Device • People were significantly more likely to take the stairs when going down (24.3%) than when going up (6.1%), 2(1, N = 3,217) = 217.22, p < .001,  = .26, odds ratio = 4.90, 95% CI [3.91, 6.13]. • SPSS gave me an odds ratio of .204 and a CI of [.163, .256]. I inverted these numbers to get ratios greater than one.

  5. Figure 1. Device x Weight

  6. Choice of device was significantly associated with weight of patron, 2(2, N = 3,217) = 11.752, p = .003,  = .06. As shown in Table 1, obese individuals used the stairs considerably less often than did others.

  7. Pairwise Comparisons • Use of the stairs did not differ significantly between overweight and normal individuals, 2(1, N = 2,907) = 1.034, p = .31, ,  = .02, odds ratio = 1.12, 95% CI [0.90, 1.38]. • Individuals of normal weight used the stairs significantly more often than did obese individuals, 2(1, N = 2,142) = 9.062, p = .003, ,  = .065, odds ratio = 1.94, 95% CI [1.25, 3.00].

  8. SPSS will mess up if you use a dichotomous predictor that is coded with numbers other than consecutive integers, such as Weight = 1 (obese) and 3 (normal). If you declare Weight to be categorical, SPSS works fine. • Overweight individuals used the stairs significantly more often than did obese individuals, 2(1, N = 1,385) = 11.815, p = .001,  = .092, odds ratio = 2.16, 95% CI [1.38, 3.38].

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