Add to ORKGrelational studies) to make causative conclusions. These methods are not defensible logically or statistically. They can only suggest hypotheses that then should be tested by proper experiments. At worst, as in the Coleman studies, they have been used to make social policy based on unjustified conclusions. The Iogical flaw of the methods of path analysis or structural equation modeling is shown. A proper evaluation of the role of investigations versus experiments is cited in the work of Cochran (as described by Rubin (19831). 1 Page and various collaborators have promoted the use of techniques applied to correlational data that ar
Determining what constitutes a causal relationship between two or more concepts, and how to infer ca...
Correlation is not causation is one of the mantras of the sciences—a cautionary warning especially t...
Economic theory is replete with causal hypotheses that are scarcely tested because economists are ge...
A shared problem across the sciences is to make sense of correlational data coming from observations...
Color poster with text and tables.The distinction between correlation and causation is emphasized i...
AbstractFor nearly a century, investigators in the social sciences have used regression models to de...
Abstract A shared problem across the sciences is to make sense of correlational data coming from obs...
ideas at Wednesday lunch-speaker series in Agricultural Economics at TAMU. These notes are an amende...
There is a deep and well-regarded tradition in economics and other social sciences as well as in the...
For decades, statistical methods, many based upon the “general linear model,” have been used to do e...
Correlation-based approaches to causal analysis contain too much irrelevant information that masks a...
Recent advances in graphical models and the logic of causation have given rise to new ways in which ...
In a backlash against the prevalence of statistical methods, recently social scientists have focused...
One of the more common techniques for measuring relationships between variables is the well-known Pe...
The Pearson correlation coefficient (r) is usually the first measure of association taught...
Determining what constitutes a causal relationship between two or more concepts, and how to infer ca...
Correlation is not causation is one of the mantras of the sciences—a cautionary warning especially t...
Economic theory is replete with causal hypotheses that are scarcely tested because economists are ge...
A shared problem across the sciences is to make sense of correlational data coming from observations...
Color poster with text and tables.The distinction between correlation and causation is emphasized i...
AbstractFor nearly a century, investigators in the social sciences have used regression models to de...
Abstract A shared problem across the sciences is to make sense of correlational data coming from obs...
ideas at Wednesday lunch-speaker series in Agricultural Economics at TAMU. These notes are an amende...
There is a deep and well-regarded tradition in economics and other social sciences as well as in the...
For decades, statistical methods, many based upon the “general linear model,” have been used to do e...
Correlation-based approaches to causal analysis contain too much irrelevant information that masks a...
Recent advances in graphical models and the logic of causation have given rise to new ways in which ...
In a backlash against the prevalence of statistical methods, recently social scientists have focused...
One of the more common techniques for measuring relationships between variables is the well-known Pe...
The Pearson correlation coefficient (r) is usually the first measure of association taught...
Determining what constitutes a causal relationship between two or more concepts, and how to infer ca...
Correlation is not causation is one of the mantras of the sciences—a cautionary warning especially t...
Economic theory is replete with causal hypotheses that are scarcely tested because economists are ge...