Extensive Study of Logistic Regression using Randomized Response Sampling

به کارگیری مدل‌های رگرسیون لجستیک ترتیبی در مطالعات کیفیت زندگی

 Background & Objectives: Due to the increasing tendency to measure the quality of life in recent years and the extensive quality of life questionnaires, it is important to determine the appropriate method of analyzing data derived from these studies. The aim of the present study was to introduce ordinal logistic regression models as an appropriate method for analyzing the data of quality of li...

Predicting the distribution of plant species using logistic regression (Case study: Garizat rangelands of Yazd province)

The aim of this research was to study the relationships between presence of plant species and environmental factors in Garizat rangelands of Yazd province and providing their predictive habitat models. After delimitation of the study area, sampling was performed using randomized-systematic method. Accordingly, vegetation data including presence and cover percentage were determined in each quadr...

Estimation of Multinomial Proportions using Higher Order Moments of Scrambling Variables in Randomized Response Sampling

Landslide susceptibility mapping using logistic regression analysis in Latyan catchment

    Every year, hundreds of people all over the world lose their lives due to landslides. Landslide susceptibility map describes the likelihood or possibility of new landslides occurring in an area, and therefore helping to reduce future potential damages. The main purpose of this study is to provide landslide susceptibility map using logistic regression model at Latyan watershed, north Iran. I...

Binary Regression With a Misclassified Response Variable in Diabetes Data

Objectives: The categorical data analysis is very important in statistics and medical sciences. When the binary response variable is misclassified, the results of fitting the model will be biased in estimating adjusted odds ratios.  The present study aimed to use a method to detect and correct misclassification error in the response variable of Type 2 Diabetes Mellitus (T2DM), applying binary ...