Add to ORKGSampling weights are a reflection of sampling design; they allow us to draw valid conclusions about population features from sample data. This paper explains the fundamentals of computing sampling weights for large-scale assessments in educational research. The relationship between the nature of complex samples and best practices in developing a set of weights to enable computation of unbiased population estimates is described. Effects of sampling weights on estimates are shown, as well as potential consequences of not using weights when analysing data from complex samples. Illustrative examples are provided in order to make it easy to understand the rationale behind the mathematical foundations
Although sampling techniques have been used effectively in education research and practice it is not...
Large surveys often use probability sampling in order to obtain representative samples, and these da...
Despite the prominent use of complex survey data and the growing popularity of machine learning meth...
Sampling weights are a reflection of sampling design; they allow us to draw valid conclusions about...
The goal of this book is to put an array of tools at the fingertips of students, practitioners, and ...
Weighting is one of the major components in survey sampling. For a given sample survey, to each uni...
A fundamental technique in survey sampling is to weight included units by the inverse of their proba...
Despite the prominent use of complex survey data and the growing popularity of machine learning meth...
This study reviewed the purpose and practice of weighting, particularly as regards disproportionatel...
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special fe...
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special fe...
The three parts of this book on survey methodology combine an introduction to basic sampling theory,...
Large scale studies frequently use complex sampling procedures, disproportionate sampling weights, a...
This tutorial gives an overview of sampling techniques commonly used in the field of education such ...
Producers have adopted marketing strategies such as topping to help cut economic losses at the proc...
Although sampling techniques have been used effectively in education research and practice it is not...
Large surveys often use probability sampling in order to obtain representative samples, and these da...
Despite the prominent use of complex survey data and the growing popularity of machine learning meth...
Sampling weights are a reflection of sampling design; they allow us to draw valid conclusions about...
The goal of this book is to put an array of tools at the fingertips of students, practitioners, and ...
Weighting is one of the major components in survey sampling. For a given sample survey, to each uni...
A fundamental technique in survey sampling is to weight included units by the inverse of their proba...
Despite the prominent use of complex survey data and the growing popularity of machine learning meth...
This study reviewed the purpose and practice of weighting, particularly as regards disproportionatel...
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special fe...
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special fe...
The three parts of this book on survey methodology combine an introduction to basic sampling theory,...
Large scale studies frequently use complex sampling procedures, disproportionate sampling weights, a...
This tutorial gives an overview of sampling techniques commonly used in the field of education such ...
Producers have adopted marketing strategies such as topping to help cut economic losses at the proc...
Although sampling techniques have been used effectively in education research and practice it is not...
Large surveys often use probability sampling in order to obtain representative samples, and these da...
Despite the prominent use of complex survey data and the growing popularity of machine learning meth...