ObjectiveTo create an efficient imputation algorithm for imputing the SF-12 physical component summary (PCS) and mental component summary (MCS) scores when patients have one to eleven SF-12 items missing.Study settingPrimary data collection was performed between 1996 and 1998.Study designMulti-pattern regression was conducted to impute the scores using only available SF-12 items (simple model), and then supplemented by demographics, smoking status and comorbidity (enhanced model) to increase the accuracy. A cut point of missing SF-12 items was determined for using the simple or the enhanced model. The algorithm was validated through simulation.Data collectionThirty-thousand-three-hundred and eight patients from 63 physician groups were surv...
Missing values, common in epidemiologic studies, are a major issue in obtaining valid estimates. Sim...
In many fields, including the field of nephrology, missing data are unfortunately an unavoidable pro...
Missing data are generally unavoidable in clinical trials (RCTs), particularly in patient reported o...
ObjectiveTo create an efficient imputation algorithm for imputing the SF-12 physical component summa...
OBJECTIVE: The SF-12 Health Survey is a 12-item questionnaire that yields two summary scores (physic...
© 2016 Jemishabye ApajeeMissing data are common in medical research. One area where missing data can...
If information on single items in the Short Form–12 health survey (SF-12) is missing, the analysis o...
Objectives Regardless of the proportion of missing values, complete-case analysis is most frequently...
Background Missing data can introduce bias in the results of randomised controlled trials (RCTs), b...
Missing data is a common occurrence in clinical research. Missing data occurs when the value of the ...
Background: Methods for handling missing data in clinical research have been getting more attentions...
One important characteristic of good data is completeness. Missing data is a major problem in the cl...
PURPOSE: Missing data are a well-known and widely documented problem in cost-effectiveness analyses ...
Abstract Laboratory data from Electronic Health Records (EHR) are often used in prediction models wh...
grantor: University of TorontoMissing data or incomplete data are very common in almost ev...
Missing values, common in epidemiologic studies, are a major issue in obtaining valid estimates. Sim...
In many fields, including the field of nephrology, missing data are unfortunately an unavoidable pro...
Missing data are generally unavoidable in clinical trials (RCTs), particularly in patient reported o...
ObjectiveTo create an efficient imputation algorithm for imputing the SF-12 physical component summa...
OBJECTIVE: The SF-12 Health Survey is a 12-item questionnaire that yields two summary scores (physic...
© 2016 Jemishabye ApajeeMissing data are common in medical research. One area where missing data can...
If information on single items in the Short Form–12 health survey (SF-12) is missing, the analysis o...
Objectives Regardless of the proportion of missing values, complete-case analysis is most frequently...
Background Missing data can introduce bias in the results of randomised controlled trials (RCTs), b...
Missing data is a common occurrence in clinical research. Missing data occurs when the value of the ...
Background: Methods for handling missing data in clinical research have been getting more attentions...
One important characteristic of good data is completeness. Missing data is a major problem in the cl...
PURPOSE: Missing data are a well-known and widely documented problem in cost-effectiveness analyses ...
Abstract Laboratory data from Electronic Health Records (EHR) are often used in prediction models wh...
grantor: University of TorontoMissing data or incomplete data are very common in almost ev...
Missing values, common in epidemiologic studies, are a major issue in obtaining valid estimates. Sim...
In many fields, including the field of nephrology, missing data are unfortunately an unavoidable pro...
Missing data are generally unavoidable in clinical trials (RCTs), particularly in patient reported o...