tlm User’s Guide: Effects under linear, logistic and Poisson regression models with transformed variables
نویسندگان
چکیده
3 Illustrative examples 4 3.1 Linear regression model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.1 Log transformation in the response . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.2 Log transformation in the explanatory variable . . . . . . . . . . . . . . . . . . . . 9 3.1.3 Log transformation in both the response and the explanatory variable . . . . . . . 13 3.1.4 Power transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.2 Logistic regression model with log transformation in the explanatory variable . . . . . . . 21
منابع مشابه
Generalized Linear Mixed Models
Generalized linear models (GLMs) represent a class of fixed effects regression models for several types of dependent variables (i.e., continuous, dichotomous, counts). McCullagh and Nelder [32] describe these in great detail and indicate that the term ‘generalized linear model’ is due to Nelder and Wedderburn [35] who described how a collection of seemingly disparate statistical techniques coul...
متن کاملبهکارگیری متغیرهای پنهان در مدل رگرسیون لجستیک برای حذف اثر همخطی چندگانه در تحلیل برخی عوامل مرتبط با سرطان پستان
Background and Objectives: Logistic regression is one of the most widely used generalized linear models for analysis of the relationships between one or more explanatory variables and a categorical response. Strong correlations among explanatory variables (multicollinearity) reduce the efficiency of model to a considerable degree. In this study we used latent variables to reduce the effects of ...
متن کاملThe Assessment of Non-Linear Effects in Clinical Research
Background: Novel models for the assessment of non-linear data are being developed for the benefit of making better predictions from the data. Objective: To review traditional and modern models. Results, and Conclusions: 1) Logit and probit transformations are often successfully used to mimic a linear model. Logistic regression, Cox regression, Poisson regression, and Markow modeling are exampl...
متن کاملPrediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis
Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods : In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were ...
متن کاملRecursive Path Models when Both Predictor and Response Variables are Categorical
Recursive path analysis is a useful tool for inference on a sequence of three or more response variables in which the causal effects of variables, if any, are in one direction. The primary objective in such analysis is to decompose the total effect of each variable into its direct and indirect components. Methods for recursive analysis of a chain of continuous variables are well developed but t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014