Q13. Gunst and Mason(1960) collected anthropometric and physical fitness measurements on 50 white male applicants to the police department of a major metropolitan city.

the SAS output from several factor analyses has been provided in the screenshots attached below. Use the provided output to decide the number of factors you feel should be retained. Explain your choice, discussing as as many criteria as you can.

Output file:-

EFA of Police Applicant Data The FACTOR Procedure Initial Factor Method: Principal Components Parallel Analysis 5 4 3 Eigenvalue 2 1 0 e 0 5 10 15 Factor e Observed Value Simulated Crit Value Eigenvalues of the Correlation Matrix: Total = 15 Average = 1 Eigenvalue Difference Proportion Cumulative 1 5.21852549 2.81172746 0.3479 0.3479 2 2.40679803 1.09411978 0.1605 0.5084 3 1.31267825 0.08160302 0.0875 0.5959 4 1.23107523 0.02722958 0.0821 0.6779 5 1.20384565 0.35594143 0.0803 0.7582 6 0.84790423 0.14315618 0.0565 0.8147 7 0.70474804 0.12633945 0.0470 0.8617 8 0.57840860 0.18486182 0.0386 0.9003 9 0.39354677 0.02535508 0.0262 0.9265 10 0.36819169 0.04160632 0.0245 0.9510 EFA of Police Applicant Data The FACTOR Procedure Initial Factor Method: Principal Factors Eigenvalues of the Reduced Correlation Matrix: Total = 9.80825494 Average = 0.65388366 Eigenvalue Difference Proportion Cumulative 15.01277837 2.96529143 0.5111 0.5111 2.04748694 1.10073964 0.2088 0.7198 2 3 0.94674730 0.15368175 0.0965 0.8164 4 0.79306556 0.10268016 0.0809 0.8972 5 0.69038540 0.27432135 0.0704 0.9676 6 0.41606405 0.11178053 0.0424 1.0100 7 0.30428352 0.08446996 0.0310 1.0410 B 8 0.21981356 0.17893960 0.0224 1.0635 9 0.04087396 0.06954357 0.0042 1.0676 10 - 02866961 0.01367703 -0.0029 1.0647 11 -04234664 0.01537489 -0.0043 1.0604 12 - 05772153 0.07905411 -0.0059 1.0545 -13677565 0.03000518 -0.0139 1.0406 13 14 15 - 16678083 0.06416863 -0.0170 1.0235 -23094946 -0.0235 1.0000 EFA of Police Applicant Data Extract 2 factors The FACTOR Procedure Initial Factor Method: Maximum Likelihood Significance Tests Based on 50 Observations Pr> Test DF Chi-Square ChiSq HO: No common factors 105 473.1958 <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient efa of police applicant data extract the procedure initial method: maximum likelihood significance tests based on observations pr> Test DF Chi-Square Chisq HO: No common factors 105 473.1958 <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient efa of police applicant data extract the procedure initial method: maximum likelihood significance tests based on observations pr> Test DF Chi-Square Chisq HO: No common factors 105 473.1958 Test DF Chi-Square Chisq HO: No common factors <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient efa of police applicant data the procedure initial method: principal components parallel analysis eigenvalue e observed value simulated crit eigenvalues correlation matrix: total="15" average="1" difference proportion cumulative reduced b extract maximum likelihood significance tests based on observations pr> Test DF Chi-Square ChiSq HO: No common factors 105 473.1958 <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient efa of police applicant data extract the procedure initial method: maximum likelihood significance tests based on observations pr> Test DF Chi-Square Chisq HO: No common factors 105 473.1958 <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient efa of police applicant data extract the procedure initial method: maximum likelihood significance tests based on observations pr> Test DF Chi-Square Chisq HO: No common factors 105 473.1958 Test DF Chi-Square Chisq HO: No common factors <.0001 ha: at least one common factor ho: factors are sufficient more needed chi-square without bartlett correction akaike information criterion schwarz bayesian tucker and lewis reliability coefficient>