Greetings statalist,
I'm planning to do a similar analyses found in: Balkus, Jennifer E., et al. "An empiric HIV risk scoring tool to predict HIV-1 acquisition in African women." JAIDS Journal of Acquired Immune Deficiency Syndromes 72.3 (2016): 333-343. (https://pdfs.semanticscholar.org/54e...30ffe9e5d5.pdf). Taken from the paper:
"To identify the combination of factors that best predicted HIV risk, we used forward and backward stepwise Cox proportional hazards model that evaluated the inclusion or exclusion of potential predictors at each step. All models were stratified by study site. The model with the lowest Akaike information criterion was chosen as the final model for the risk score. Individual predictors included in the final model were assigned a score by dividing the coefficient for the predictor in the final model by the lowest coefficient among all predictors in the model and rounding to the nearest integer. The sum of the values for each predictor represented the total score for each participant, and the HIV incidence for each total score category was calculated. The predictive ability of the total score and each predictor was assessed by calculating area under the receiver operating characteristic curve. The score was internally validated using 10-fold cross- validation, and the area under the curve (AUC) for the final model was compared with the mean AUC of the 10 different models. Additional performance characteristics (sensitivity, specificity, positive predictive value, and negative predictive value) were calculated using risk score cut-points that corresponded to an HIV incidence in the risk score category of approximately >3% and >5%. Incidence curves were generated to assess cumulative HIV incidence by risk score cut-point."
Conceptually, I understand what was done. Unfortunately, I do not know how to execute the analyses after the regression models. I've read similar papers that multiplied the regression coefficient by 10 and then round to the nearest integer. I would greatly appreciate assistance in identifying the STATA commands associated with executing this: "Individual predictors included in the final model were assigned a score by dividing the coefficient for the predictor in the final model by the lowest coefficient among all predictors in the model and rounding to the nearest integer." as well as "The score was internally validated using 10-fold cross- validation, and the area under the curve (AUC) for the final model was compared with the mean AUC of the 10 different models."
Thanks so much for your assistance.
I'm planning to do a similar analyses found in: Balkus, Jennifer E., et al. "An empiric HIV risk scoring tool to predict HIV-1 acquisition in African women." JAIDS Journal of Acquired Immune Deficiency Syndromes 72.3 (2016): 333-343. (https://pdfs.semanticscholar.org/54e...30ffe9e5d5.pdf). Taken from the paper:
"To identify the combination of factors that best predicted HIV risk, we used forward and backward stepwise Cox proportional hazards model that evaluated the inclusion or exclusion of potential predictors at each step. All models were stratified by study site. The model with the lowest Akaike information criterion was chosen as the final model for the risk score. Individual predictors included in the final model were assigned a score by dividing the coefficient for the predictor in the final model by the lowest coefficient among all predictors in the model and rounding to the nearest integer. The sum of the values for each predictor represented the total score for each participant, and the HIV incidence for each total score category was calculated. The predictive ability of the total score and each predictor was assessed by calculating area under the receiver operating characteristic curve. The score was internally validated using 10-fold cross- validation, and the area under the curve (AUC) for the final model was compared with the mean AUC of the 10 different models. Additional performance characteristics (sensitivity, specificity, positive predictive value, and negative predictive value) were calculated using risk score cut-points that corresponded to an HIV incidence in the risk score category of approximately >3% and >5%. Incidence curves were generated to assess cumulative HIV incidence by risk score cut-point."
Conceptually, I understand what was done. Unfortunately, I do not know how to execute the analyses after the regression models. I've read similar papers that multiplied the regression coefficient by 10 and then round to the nearest integer. I would greatly appreciate assistance in identifying the STATA commands associated with executing this: "Individual predictors included in the final model were assigned a score by dividing the coefficient for the predictor in the final model by the lowest coefficient among all predictors in the model and rounding to the nearest integer." as well as "The score was internally validated using 10-fold cross- validation, and the area under the curve (AUC) for the final model was compared with the mean AUC of the 10 different models."
Thanks so much for your assistance.
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