Download full text
(external source)
Citation Suggestion
Please use the following Persistent Identifier (PID) to cite this document:
https://doi.org/10.12758/mda.2017.07
Exports for your reference manager
Simultaneous Feedback Models with Macro-Comparative Cross-Sectional Data
[journal article]
Abstract Social scientists often work with theories of reciprocal causality. Sometimes theories suggest that reciprocal causes work simultaneously, or work on a time-scale small enough to make them appear simultaneous. Researchers may employ simultaneous feedback models to investigate such theories, although... view more
Social scientists often work with theories of reciprocal causality. Sometimes theories suggest that reciprocal causes work simultaneously, or work on a time-scale small enough to make them appear simultaneous. Researchers may employ simultaneous feedback models to investigate such theories, although the practice is rare in cross-sectional survey research. This paper discusses the certain conditions that make these models possible if not desirable using such data. This methodological excursus covers the construction of simultaneous
feedback models using a structural equation modeling perspective. This allows the researcher to test if a simultaneous feedback theory fits survey data, test competing hypotheses and engage in macro-comparisons. This paper presents methods in a manner and language amenable to the practicing social scientist who is not a statistician or matrix mathematician. It demonstrates how to run models using three popular software programs (MPlus, Stata and R), and an empirical example using International Social Survey Program data.... view less
Keywords
survey research; comparative research; cross-sectional study; estimation; correlation; regression
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
simultaneous feedback model; cross-sectional data; macro-comparative research; structural equation modeling; reciprocal causality; Mplus; Stata; R (lavaan)
Document language
English
Publication Year
2018
Page/Pages
p. 265-307
Journal
Methods, data, analyses : a journal for quantitative methods and survey methodology (mda), 12 (2018) 2
Issue topic
Comparative Survey Analysis: Models, Techniques, and Applications
ISSN
2190-4936
Status
Published Version; peer reviewed