Estimating a Three-Level Latent Variable Regression Model With Cross-Classified Multiple Membership Data
نویسندگان
چکیده
منابع مشابه
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 ...
متن کاملA Multi-Level Cross-Classified Model for Discrete Response Variables
In many spatial analysis contexts, the variable of interest is discrete and there is spatial clustering of observations. This paper formulates a model that accommodates clustering along more than one dimension in the context of a discrete response variable. For example, in a travel mode choice context, individuals are clustered by both the home zone in which they live as well as by their work l...
متن کاملMultiple Fuzzy Regression Model for Fuzzy Input-Output Data
A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...
متن کاملComparing Three Regression Models for Reconstructing Groundwater Level Data (A Case Study)
The base for hydrology studies is accurate data. However, the gaps and shortage of sufficient data exist n the most hydrology data such as underground water data as the most important and cheapest water source, lack of data take places due to various reasons such as Inability to measure and faille to register statistics. Missing data or incorrect statistics, Therefore, estimating the missin...
متن کاملBayesian latent variable models for median regression on multiple outcomes.
Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Methodology
سال: 2018
ISSN: 1614-1881,1614-2241
DOI: 10.1027/1614-2241/a000143