Download Advances in Configural Frequency Analysis (Methodology In by Alexander von Eye PhD, Patrick Mair, Eun-Young Mun PhD PDF

By Alexander von Eye PhD, Patrick Mair, Eun-Young Mun PhD

Utilizing real-world facts examples, this authoritative publication indicates how you can use the newest configural frequency research (CFA) concepts to investigate specific facts. a few of the concepts are awarded the following for the 1st time. unlike tools that target relationships between variables, similar to log-linear modeling, CFA permits researchers to guage modifications and alter at the extent of person cells in a desk. Illustrated are how you can establish and try for cellphone configurations which are both constant with or opposite to hypothesized styles (the varieties and antitypes of CFA); keep an eye on for capability covariates that will impression saw effects; strengthen leading edge prediction versions; deal with questions of moderation and mediation; and learn in depth longitudinal info. The booklet additionally describes unfastened software program purposes for executing CFA. (20110302)

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Example text

2 Data Examples In the following paragraphs, we present two data examples. The first involves data from two raters. The second involves data from three raters. Data Example 1: In the following example, we analyze data from a study on the agreement of raters on the qualification of job applicants in a large agency in the United States1. A total of 466 interview protocols was examined by two evaluators, A and B. Each evaluator independently indicated on a six-point ordinal scale the degree to which an applicant was close to the profile specified in the advertisement for the position, with 1 indicating very good match and 6 indicating lack of match.

Quasi-Independence Model for the Exploration of Disagreement: For example, in the context of rater training, it can be important to know where raters disagree. Disagreement beyond chance may lead to additional training or redefining categories of rating scales. A CFA model that is suited for the exploration of disagreement cells is the log-linear quasi-independence model. For two raters, this model is ˆ = λ + λA + λB + log m λk , k where the first three terms on the right-hand side of the equation are the same as in the first order CFA base model.

There are two groups of CFA base models. The first includes most of the original CFA models (Krauth & Lienert, 1973). It is called the group of global CFA base models. These models do not distinguish between variables of different status. By implication, there is no grouping of variables in predictors and criteria or dependent and independent variables. There is not even the separation of groups of variables that are related to one another. All variables have the same status. This group of models has its parallel in exploratory factor analysis, correspondence analysis, or in multidimensional scaling.

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