Series: Basic Statistics for Busy Clinicians (vii) Logistic Regression Models

SERIES: BASIC STATISTICS FOR BUSY CLINICIANS (X) Bias in clinical epidemiological study designs

Combined subject table of contents

Statistics ANOVA and related Multiple imputation Basic statistics Multivariate analysis of variance and Binary outcomes related techniques Categorical outcomes Nonlinear regression Censored and truncated regression models Nonparametric statistics Cluster analysis Ordinal outcomes Correspondence analysis Other statistics Count outcomes Pharmacokinetic statistics Discriminant analysis Power and s...

Prediction 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 ...

Comparison of ordinary logistic regression and robust logistic regression models in modeling of pre-diabetes risk factors

Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors. Methods: This is a cross-sectional study and conducted on 6460 people, over ...

BASIC STATISTICS FOR BUSY CLINICIANS ( V ) Statistical inference : Hypothesis testing

The aim of statistical inference is to predict the parameters of a population, based on a sample of data. Inferential statistics encompasses the estimation of parameters and model predictions. The present article describes the hypothesis tests or statistical significance tests most commonly used in healthcare research. & 2010 SEICAP. Published by Elsevier España, S.L. All rights reserved.