Multivariable causal modeling in alcohol use research
Bibliographic Data
| ID | 7668807 |
|---|---|
| Authors | John R Nesselroade (Pennsylvania State University, corresponding author), J Jack McArdle (University of Virginia) |
| Year | 1985 |
| Volume | 32 |
| Issue | 3-4 |
| Pages | 272-296 |
| Publication date | 1985-09-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Biodemography and Social Biology (JOURNAL) |
| Journal identifiers | ISSN: 1948-5565 • E-ISSN: 1948-5573 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/19485565.1985.9988614 |
| PMID | 3837353 |
| OpenAlex | W2033262365 |
| Language | EN |
| Citations received | 1 |
| References cited | 46 |
For a variety of reasons, multivariate approaches to the study of behavioral phenomena have received increased attention during the past several decades. These include: (1) greater awareness of the value of studying relationships among concepts defined over several variables rather than focusing on single variates as indicators of important constructs; (2) more sophistication in mathematical and statistical analysis; and (3) wider availability of computers and improved computer programs. Although once largely identified with "exploratory" analysis methods, multivariate applications are now found across a wide range of exploratory to explanatory activities. Currently, one of the most popular applications of the multivariate orientation concerns the development and testing of explanatory models of relationships among variables that feature a distinction between latent and manifest variables. To some extent these methods have already been employed to model: (1) drug and alcohol use; (2) genetics‐behavior relationships; and (3) case study dynamics. In both exploratory, descriptive application and hypothesis testing multivariate methods promise to be of considerable value in developing a fuller understanding of biological and behavioral mechanisms involved in patterns of alcohol use
Alcohol · Causal model · Econometrics · Multivariable calculus · Statistics · Advanced Causal Inference Techniques · Bayesian Modeling and Causal Inference · Chemistry · Computer Science · Engineering · Mathematics
A Dynamic Factor Model for the Analysis of Multivariate Time Series
"General Intelligence," Objectively Determined and Measured
Asymptotically distribution‐free methods for the analysis of covariance structures
Multivariate Analysis with Latent Variables
Notes on Factorial Invariance
The Theory of Relativity
Diagnosis of Alcoholism
Dimensions of Treatment Outcome; A Factor-Analytic Study of Alcoholics' Responses to a Follow-up Questionnaire
On the Madness in His Method
Some Cautions Concerning The Application Of Causal Modeling Methods
Figural Creativity, Intelligence, And Personality In Children
To Set The Stage
Multiple factor analysis
Application of structural modeling with latent variables to adolescent drug use
Application of structural modeling with latent variables to adolescent drug use
Intraindividual differences dimensions of mood change during pregnancy identified in five P-technique factor analyses
Weighting predictors in linear models
Correlation and Causation
The two disciplines of scientific psychology
Assessment of alcohol use with multidimensional concepts and measures
The structure of mood change
Beyond the two disciplines of scientific psychology
Weighting predictors in linear models
When not to factor analyze
| Citations per year | 0.03 |
|---|---|
| Citation span | 1987 - 1987 (1) |
| Highly cited | No |