True Score or Factor Models

A Secondary Analysis of the ALLBUS-Test-Retest Data

Datos Bibliográficos

ID2331622
AutoresWillem E Saris (0000-0002-2513-8589, University of Amsterdam), Bas Van Den Putte (0000-0002-3635-6880, University of Amsterdam)
Año1988
Volumen17
Número2
Páginas123-157
Fecha de publicación1988-11-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSociological Methods & Research (JOURNAL)
Identificadores de la revistaISSN: 0049-1241 • E-ISSN: 1552-8294
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/0049124188017002001
OpenAlexW2003747183
IdiomaEN
Citas recibidas6
Referencias citadas13

In the February 1987 issue of Sociological Methods and Research several articles were published that dealt with the same data set. These data focused on attitudes toward guest workers. The purpose of that study was to demonstrate the application of measurement models, especially with respect to random measurement error, on large-scale survey data. Since we think that such studies are very valuable, we want to continue the discussion on measurement models by applying alternative models to the same data. We show that quite different models fit the same data set and that these models lead to quite different interpretations. In doing so we will use some tests that we think should be applied in order to differentiate between measurement or true score models and factor analysis models. In this article we show that the resulting models and interpretations of the data can vary quite a lot depending on whether one uses a true score model or a factor model. The substantive result of these analyses is that it seems possible to distinguish two types of opinions. One type we have called the first reaction, and the other type is called a more seriously considered opinion. These two opinions differ systematically from each other and therefore the results of research using the one or the other opinion will also differ

Data science · Data set · Econometrics · Order (exchange) · Scale (ratio) · Set (abstract data type) · Statistics · Artificial Intelligence · Computer Science · Mathematics · Social and Intergroup Psychology