scholarly journals Time-Efficient Adaptive Measurement of Change

2019 ◽  
pp. 15-34
Author(s):  
Matthew Finkelman ◽  
Chun Wang
Keyword(s):  
Measurement Of Change ◽  
Adaptive Measurement

Item Selection and Hypothesis Testing for the Adaptive Measurement of Change

2010 ◽  
Vol 34 (4) ◽  
pp. 238-254 ◽  
Author(s):  
Matthew D. Finkelman ◽  
David J. Weiss ◽  
Gyenam Kim-Kang
Keyword(s):  
Hypothesis Testing ◽  
Item Selection ◽  
Measurement Of Change ◽  
Adaptive Measurement

Adaptive Measurement of Individual Change

2008 ◽  
Vol 216 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Gyenam Kim-Kang ◽  
David J. Weiss
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Entire Range ◽  
Individual Change ◽  
Measurement Of Change ◽  
Adaptive Measurement

Adaptive measurement of change (AMC) was investigated by examining the recovery of true change. Monte Carlo simulation was used to compare three conventional testing (CT) methods with AMC. The CTs estimated individual change moderately well when the test was highly discriminating and when the θ level matched the test difficulty. However, AMC measured individual change equally well across the entire range of θ. AMC with more discriminating items produced the most precise estimates of individual change. AMC was shown to be superior to CTs under all conditions examined. In addition, AMC is efficient – it can dramatically reduce the number of items necessary to measure individual change. The results indicate that AMC is a viable and effective method for measuring individual change.

Robustness of Adaptive Measurement of Change to Item Parameter Estimation Error

2021 ◽  
pp. 001316442110339
Author(s):  
Allison W. Cooperman ◽  
David J. Weiss ◽  
Chun Wang
Keyword(s):  
Parameter Estimation ◽  
False Positive ◽  
Estimation Error ◽  
Latent Trait ◽  
Item Bank ◽  
Item Parameter ◽  
Individual Change ◽  
Measurement Of Change ◽  
Item Parameter Estimation ◽  
Adaptive Measurement

Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests—a Z test, likelihood ratio test, and score ratio index—have demonstrated desirable statistical properties in this context, including low false positive rates and high true positive rates. However, the extant AMC research has assumed that the item parameter values in the simulated item banks were devoid of estimation error. This assumption is unrealistic for applied testing settings, where item parameters are estimated from a calibration sample before test administration. Using Monte Carlo simulation, this study evaluated the robustness of the common AMC hypothesis tests to the presence of item parameter estimation error when measuring omnibus change across four testing occasions. Results indicated that item parameter estimation error had at most a small effect on false positive rates and latent trait change recovery, and these effects were largely explained by the computerized adaptive testing item bank information functions. Differences in AMC performance as a function of item parameter estimation error and choice of hypothesis test were generally limited to simulees with particularly low or high latent trait values, where the item bank provided relatively lower information. These simulations highlight how AMC can accurately measure intra-individual change in the presence of item parameter estimation error when paired with an informative item bank. Limitations and future directions for AMC research are discussed.

scholarly journals Controlling response dependence in the measurement of change using the Rasch model

2017 ◽  
Vol 27 (12) ◽  
pp. 3709-3725 ◽  
Author(s):  
David Andrich
Keyword(s):  
Rasch Model ◽  
Real Data ◽  
Repeated Measurements ◽  
Measurement Of Change ◽  
Location Parameters ◽  
Response Dependence ◽  
The Individual ◽  
First Time ◽  
The Rasch Model ◽  
Research And Policy

The advantages of using person location estimates from the Rasch model over raw scores for the measurement of change using a common test include the linearization of scores and the automatic handling of statistical properties of repeated measurements. However, the application of the model requires that the responses to the items are statistically independent in the sense that the specific responses to the items on the first time of testing do not affect the responses at a second time. This requirement implies that the responses to the items at both times of assessment are governed only by the invariant location parameters of the items at the two times of testing and the location parameters of each person each time. A specific form of dependence that is pertinent when the same items are used is when the observed response to an item at the second time of testing is affected by the response to the same item at the first time, a form of dependence which has been referred to as response dependence. This paper presents the logic of applying the Rasch model to quantify, control and remove the effect of response dependence in the measurement of change when the same items are used on two occasions. The logic is illustrated with four sets of simulation studies with dichotomous items and with a small example of real data. It is shown that the presence of response dependence can reduce the evidence of change, a reduction which may impact interpretations at the individual, research, and policy levels.

The Sensitivity of the Beck Depression Inventory to Changes of Symptomatology

1974 ◽  
Vol 125 (585) ◽  
pp. 184-185 ◽  
Author(s):  
D. A. W. Johnson ◽  
B. B. Heather
Keyword(s):  
General Practice ◽  
Clinical Research ◽  
Beck Depression Inventory ◽  
Depressive Mood ◽  
Measurement Of Change ◽  
Practice Population ◽  
Absolute Measure

Despite the popularity of the Beck Depression Inventory (Beck et al., 1961), only Salkind (1969) has attempted to validate this instrument for a general practice population. For some purposes, particularly clinical research, measurement of change in a depressive mood is more important than an absolute measure. So far only Little and McPhail (1973) have considered this aspect of use.

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