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Also, reliability is a property of the scores of a measure rather than the measure itself and are thus said to be sample dependent. Reliability estimates from one sample might differ from those of a second sample (beyond what might be expected due to sampling variations) if the second sample is drawn from a different population because the true ...
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations.It is used to determine the reliability (i.e., reproducibility) of measurements under specific conditions.
In other words, the relevance of external and internal validity to a research study depends on the goals of the study. Furthermore, conflating research goals with validity concerns can lead to the mutual-internal-validity problem, where theories are able to explain only phenomena in artificial laboratory settings but not the real world. [13] [14]
Alpha is also a function of the number of items, so shorter scales will often have lower reliability estimates yet still be preferable in many situations because they are lower burden. An alternative way of thinking about internal consistency is that it is the extent to which all of the items of a test measure the same latent variable. The ...
Recommended approaches to test for discriminant validity on the construct level are AVE-SE comparisons (Fornell & Larcker, 1981; note: hereby the measurement error-adjusted inter-construct correlations derived from the CFA model should be used rather than raw correlations derived from the data.) [2] and the assessment of the HTMT ratio ...
In a study of concurrent validity the test is administered at the same time as the criterion is collected. This is a common method of developing validity evidence for employment tests: A test is administered to incumbent employees, then a rating of those employees' job performance is, or has already been, obtained independently of the test ...
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon.
This example of a survival tree analysis uses the R package "rpart". [8] The example is based on 146 stage C prostate cancer patients in the data set stagec in rpart. Rpart and the stagec example are described in Atkinson and Therneau (1997), [9] which is also distributed as a vignette of the rpart package. [8] The variables in stages are: