stata modules for calculating novel predictive performance indices for logistic models
نویسندگان
چکیده
results the command is addpred for logistic regression models. conclusions the stata package provided herein can encourage the use of novel methods in examining predictive capacity of ever-emerging plethora of novel biomarkers. materials and methods we have written a stata command that is intended to help researchers obtain cut point-free and cut point-based net reclassification improvement index and (nri) and relative and absolute integrated discriminatory improvement index (idi) for logistic-based regression analyses.we applied the commands to a real data on women participating the tehran lipid and glucose study (tlgs) to examine if information of a family history of premature cvd, waist circumference, and fasting plasma glucose can improve predictive performance of the framingham’s “general cvd risk” algorithm. objectives lack of user-friendly statistical software has restricted implementation of novel model assessment methods while examining novel biomarkers. we intended, thus, to develop a user-friendly software that could be used by researchers with few programming skills. background prediction is a fundamental part of prevention of cardiovascular diseases (cvd). the development of prediction algorithms based on the multivariate regression models loomed several decades ago. parallel with predictive models development, biomarker researches emerged in an impressively great scale. the key question is how best to assess and quantify the improvement in risk prediction offered by new biomarkers or more basically how to assess the performance of a risk prediction model. discrimination, calibration, and added predictive value have been recently suggested to be used while comparing the predictive performances of the predictive models’ with and without novel biomarkers.
منابع مشابه
Stata Modules for Calculating Novel Predictive Performance Indices for Logistic Models
BACKGROUND Prediction is a fundamental part of prevention of cardiovascular diseases (CVD). The development of prediction algorithms based on the multivariate regression models loomed several decades ago. Parallel with predictive models development, biomarker researches emerged in an impressively great scale. The key question is how best to assess and quantify the improvement in risk prediction...
متن کاملPerformance Evaluation of Dynamic Modulus Predictive Models for Asphalt Mixtures
Dynamic modulus characterizes the viscoelastic behavior of asphalt materials and is the most important input parameter for design and rehabilitation of flexible pavements using Mechanistic–Empirical Pavement Design Guide (MEPDG). Laboratory determination of dynamic modulus is very expensive and time consuming. To overcome this challenge, several predictive models were developed to determine dyn...
متن کاملa new approach to credibility premium for zero-inflated poisson models for panel data
هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
15 صفحه اولFitting Stereotype Logistic Regression Models for Ordinal Response Variables in Educational Research (Stata)
The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not ...
متن کاملData Mining Based Predictive Models for Overall Health Indices
In this study, we infer health care indices of individuals using their pharmacy medical and prescription claims. Specifically, we focus on the widely used Charlson Index. We use data mining techniques to formulate the problem of classifying Charlson Index (CI) and build predictive models to predict individual health index score. First, we present comparative analyses of several classification a...
متن کاملPredictive factors for loneliness in female high school students; an unvariate and multivariate logistic regression analysis
Background and aims: Loneliness typically includes anxious feelings. It is particularly relevant to adolescence period. It has effect on physical and mental health. The present study aimed to identify the predictive factors of loneliness among high schools female students. Methods: A cross– sectional survey was carried out among high schools female students in Ilam during the academic year 201...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
international journal of endocrinology and metabolismجلد ۱۴، شماره ۱، صفحات ۰-۰
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023