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Multinomial Logistic Regression. 3 or more groups Students in Engineering at ECU 1.Persisters – still in the program after 2 years 2.Left in Good Standing.

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Presentation on theme: "Multinomial Logistic Regression. 3 or more groups Students in Engineering at ECU 1.Persisters – still in the program after 2 years 2.Left in Good Standing."— Presentation transcript:

1 Multinomial Logistic Regression

2 3 or more groups Students in Engineering at ECU 1.Persisters – still in the program after 2 years 2.Left in Good Standing (GPA  2.00) 3.Left in Poor Standing (GPA < 2.00)

3 Predictor Variables SAT Scores (Verbal and Quantitative) ALEKS Scores – calculus readiness High School GPA NEO Five-Factor Inventory (5 variables) Nowicki–Duke Locus of Control (high = external)

4 Standardize Predictors

5 Analyze, Regression, Multinomial Logistic

6 Ask for a classification table

7 Output Case Processing Summary N Marginal Percentage Groups Poor6826.6% Good8533.2% Stay10340.2% Valid256100.0%

8 Model Fitting Information Model Model Fitting CriteriaLikelihood Ratio Tests -2 Log LikelihoodChi-SquaredfSig. Intercept Only555.273 Final473.25382.02020.000

9 Pseudo R-Square Cox and Snell.274 Nagelkerke.310 McFadden.148

10 Likelihood Ratio Tests Effect Model Fitting Criteria Likelihood Ratio Tests -2 Log Likelihood of Reduced Model Chi-SquaredfSig. Intercept 488.05314.8002.001 ZMSAT 480.0106.7572.034 ZVSAT 475.9472.6942.260 ZHSGPA 493.74820.4952.000 ZALEKS 482.5469.2922.010 ZLOC 475.3502.0962.351 ZNEOOpen 473.641.3882.824 ZNEOC 488.93315.6802.000 ZNEOE 473.844.5912.744 ZNEOA 473.951.6982.705 ZNEON 475.2361.9832.371

11 k-1 sets of coefficients Earlier we designated the reference group to be that with the highest code, the persisters. Each of the other two groups will be contrasted with that group.

12 Groups a B Std. Error WalddfSig.Exp(B) Poor Intercept-.734.21212.0341.001 ZMSAT-.249.2261.2151.270.780 ZVSAT-.049.217.0511.820.952 ZHSGPA-.838.20217.1611.000.433 ZALEKS-.619.2088.8331.003.538 ZLOC-.087.211.1721.678.916 ZNEOOpen.125.204.3731.5411.133 ZNEOC-.807.23012.2981.000.446 ZNEOE.008.216.0011.9721.008 ZNEOA-.030.207.0221.883.970 ZNEON-.289.2521.3141.252.749 Those who left in poor standing versus those who persisted.

13 Groups a B Std. Error WalddfSig.Exp(B) Good Intercept-.109.159.4681.494 ZMSAT-.487.1926.4481.011.614 ZVSAT.239.1731.9131.1671.270 ZHSGPA-.171.1651.0711.301.843 ZALEKS-.215.1711.5731.210.807 ZLOC.189.1781.1251.2891.208 ZNEOOpen.023.164.0201.8881.023 ZNEOC-.044.194.0521.819.956 ZNEOE.126.177.5051.4771.134 ZNEOA-.145.182.6311.427.865 ZNEON-.233.1971.3921.238.792

14 Classification Observed Predicted PoorGoodStay Percent Correct Poor4412 64.7% Good18343340.0% Stay12197269.9% Overall Percentage28.9%25.4%45.7%58.6%

15 REGWQ Variable GroupConscientiousnessHS GPAALEKSMath SAT Persisting33.23 A 3.21 A 59.82 A 583.30 A LGS32.24 A 3.14 A 52.34 B 554.00 B LPS28.21 B 2.94 B 46.28 B 552.79 B Note: Within each column, means sharing a superscript are not significantly different from each other. N = 256. A Posteriori Pairwise Comparisons Between Group Means.

16 Presenting the Results Please see the associated document.the associated document


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