Finding
Dichotomizing a continuous variable in statistical analysis leads to underpowered of a test and reduced performance of a prediction model.
Paper
Outcomes Of Dichotomizing A Continuous Variable In The Psychiatric Early Readmission Prediction Model
Observational Study
Citations: 1
Full text
Semantic ScholarAbstract
Objective: To illustrate the results of dichotomizing a continuous variable in a prediction model. Method: 202 patients who were discharged from the psychiatric ward, University Malaya Medical Centre (UMMC) from 27th August 2007 to 15th April 2008 were recruited. The general psychopathology was measured with Brief Psychiatric Rating Scale (BPRS-24). The information on age, gender, race, marital status, occupation, psychiatric diagnosis, first onset, electroconvulsive therapy, substance use, oral treatment and depot injection were collected. On follow up, the patients who had early readmission ( Result: Both univariate tests showed that BPRS score was significantly associated with early readmission. The power of the test reduced from 0.97 to 0.65 after dichotomizing the BPRS score with alpha of 0.05. The performance of the logistic regression model decreased (AUC: 0.749 to 0.728; Nagelkerke R2: 0.244 to 0.211) and significance of hypothesis testing reduced (P value: 0.002 to 0.036) after dichotomization. Conclusion: Dichotomizing a continuous variable in statistical analysis leads to underpowered of a test and reduced performance of a prediction model. Keywords: Dichotomizing, prediction model, continuous variable
Authors
C. G. Ng
Journal
The Malaysian Journal of Psychiatry