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reliability

Member Training: Practical Advice for Establishing Reliability and Validity

by guest

How do you know your variables are measuring what you think they are? And how do you know they’re doing it well?

A key part of answering these questions is establishing reliability and validity of the measurements that you use in your research study. But the process of establishing reliability and validity is confusing. There are a dizzying number of choices available to you.

[Read more…] about Member Training: Practical Advice for Establishing Reliability and Validity

Tagged With: composite measures, composite score, Criterion and construct valitdity, Information Criterion, inter rater reliability, internal consistency, internal structure, Literature Review, measurement, parallel forms, patient reported, reliability, researcher evaluations, test-retest reliability, validity

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Member Training: Reporting Structural Equation Modeling Results

by Jeff Meyer

The last, and sometimes hardest, step for running any statistical model is writing up results.

As with most other steps, this one is a bit more complicated for structural equation models than it is for simpler models like linear regression.

Any good statistical report includes enough information that someone else could replicate your results with your data.

[Read more…] about Member Training: Reporting Structural Equation Modeling Results

Tagged With: CFA, discriminant analysis, error term, factor loadings, Intercept, Latent Growth Curve Model, mean, mediation, parameter estimates, principal component analysis, reliability, reporting, SEM, Structural Equation Modeling

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Life After Exploratory Factor Analysis: Estimating Internal Consistency

by guest 2 Comments

by Christos Giannoulis, PhD

After you are done with the odyssey of exploratory factor analysis (aka a reliable and valid instrument)…you may find yourself at the beginning of a journey rather than the ending.

The process of performing exploratory factor analysis usually seeks to answer whether a given set of items form a coherent factor (or often several factors). If you decide on the number and type of factors, the next step is to evaluate how well those factors are measured.

[Read more…] about Life After Exploratory Factor Analysis: Estimating Internal Consistency

Tagged With: Coefficient alpha, Cronbach's alpha, Exploratory Factor Analysis, Factor Analysis, latent variable, reliability, scale reliability

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What Is Reliability and Why Does It Matter

by Audrey Schnell 1 Comment

by Audrey Schnell, PhD

Some variables are straightforward to measure without error – blood pressure, number of arrests, whether someone knew a word in a second language.

But many – perhaps most –  are not. Whenever a measurement has a potential for error, a key criterion for the soundness of that measurement is reliability.

Think of reliability as consistency or repeatability in measurements. [Read more…] about What Is Reliability and Why Does It Matter

Tagged With: inter rater reliability, internal consistency, reliability, test-retest reliability

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Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?

by Karen Grace-Martin Leave a Comment

There are many rules of thumb in statistical analysis that make decision making and understanding results much easier.

Have you ever stopped to wonder where these rules came from, let alone if there is any scientific basis for them? Is there logic behind these rules, or is it propagation of urban legends?

In this webinar, we’ll explore and question the origins, justifications, and some of the most common rules of thumb in statistical analysis, like:

[Read more…] about Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?

Tagged With: effect size, reliability, results, rules of thumb, sample size, Statistical analysis

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Member Training: Confirmatory Factor Analysis

by guest Leave a Comment

There are two main types of factor analysis: exploratory and confirmatory. Exploratory factor analysis (EFA) is data driven, such that the collected data determines the resulting factors. Confirmatory factor analysis (CFA) is used to test factors that have been developed a priori.

Think of CFA as a process for testing what you already think you know.

CFA is an integral part of structural equation modeling (SEM) and path analysis. The hypothesized factors should always be validated with CFA in a measurement model prior to incorporating them into a path or structural model. Because… garbage in, garbage out.

CFA is also a useful tool in checking the reliability of a measurement tool with a new population of subjects, or to further refine an instrument which is already in use.

Elaine will provide an overview of CFA. She will also [Read more…] about Member Training: Confirmatory Factor Analysis

Tagged With: a priori, Confirmatory Factor Analysis, Factor Analysis, reliability, Structural Equation Modeling

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