The authors describe and analyze some issues in understanding causality from panel designs. They focus on complications that arise when multivariate panel models are measured with either random or systematic errors. The analysis is illustrated with panel from the U.N. of education and economic data from 96 countries. They conclude that new statistics, to be developed or imported from other disciplines are needed to deal with measurement error in substantive panel data
<p>Abstract copyright data collection owner.</p>In this project, data were used from: - the British ...
In this manuscript we seek to relax some of the traditional assumptions associated with the estimati...
This article compares a general cross-lagged model (GCLM) to other panel data methods based on thei...
Panel data consist of measurements taken from several individuals over time. Correlation among measu...
Measurement error is a pervasive problem in economics and other social and behavioral sciences. Esti...
This paper demonstrates that measurement error can conspire with multicollinearity among explanatory...
My dissertation consists three independent chapters. The first chapter studies the asymptotic proper...
The authors describe methodological issues of panel analysis designs; in particular, autocorrelation...
Establishing causal relationships is arguably the most important task of the social sciences. While ...
In this user friendly introduction, European and American experts in the field join forces to explai...
First published online 15 September 2015.We discuss the problem of random measurement error in two v...
Measurement error causes a bias towards zero when estimating a panel data linear regression model. T...
Zero correlation between measurement error and model error has been assumed in existing panel data m...
This paper proposes a method to simultaneously estimate both measurement and nonresponse errors for ...
Longitudinal data is essential for understanding how the world around us changes. Most theories in t...
<p>Abstract copyright data collection owner.</p>In this project, data were used from: - the British ...
In this manuscript we seek to relax some of the traditional assumptions associated with the estimati...
This article compares a general cross-lagged model (GCLM) to other panel data methods based on thei...
Panel data consist of measurements taken from several individuals over time. Correlation among measu...
Measurement error is a pervasive problem in economics and other social and behavioral sciences. Esti...
This paper demonstrates that measurement error can conspire with multicollinearity among explanatory...
My dissertation consists three independent chapters. The first chapter studies the asymptotic proper...
The authors describe methodological issues of panel analysis designs; in particular, autocorrelation...
Establishing causal relationships is arguably the most important task of the social sciences. While ...
In this user friendly introduction, European and American experts in the field join forces to explai...
First published online 15 September 2015.We discuss the problem of random measurement error in two v...
Measurement error causes a bias towards zero when estimating a panel data linear regression model. T...
Zero correlation between measurement error and model error has been assumed in existing panel data m...
This paper proposes a method to simultaneously estimate both measurement and nonresponse errors for ...
Longitudinal data is essential for understanding how the world around us changes. Most theories in t...
<p>Abstract copyright data collection owner.</p>In this project, data were used from: - the British ...
In this manuscript we seek to relax some of the traditional assumptions associated with the estimati...
This article compares a general cross-lagged model (GCLM) to other panel data methods based on thei...