Biomedical subjects

Cees A W Glas

Publications and source records attributed to Cees A W Glas.

5 recordsLinked to original sources

PubMed2005

The Academic Medical Center Linear Disability Score (ALDS) item bank: item response theory analysis in a mixed patient population.

BACKGROUND: Currently, there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life. This paper examines the measurement properties of the Academic Medical Center linear disability score item bank in a mixed population. METHODS: This paper uses item response theory to analyse data on 115 of 170 items from a total of 1002 respondents. These were: 551 (55%) residents of supported housing, residential care or nursing homes; 235 (23%) patients with chronic pain; 127 (13%) inpatients on a neurology ward following a stroke; and 89 (9%) patients suffering from Parkinson's disease. RESULTS: Of the 170 items, 115 were judged to be clinically relevant. Of these 115 items, 77 were retained in the item bank following the item response theory analysis. Of the 38 items that were excluded from the item bank, 24 had either been presented to fewer than 200 respondents or had fewer than 10% or more than 90% of responses in the category 'can carry out'. A further 11 items had different measurement properties for younger and older or for male and female respondents. Finally, 3 items were excluded because the item response theory model did not fit the data. CONCLUSION: The Academic Medical Center linear disability score item bank has promising measurement characteristics for the mixed patient population described in this paper. Further studies will be needed to examine the measurement properties of the item bank in other populations.

Academic Medical Centers↗

PubMed2005

Modelling non-ignorable missing-data mechanisms with item response theory models.

A model-based procedure for assessing the extent to which missing data can be ignored and handling non-ignorable missing data is presented. The procedure is based on item response theory modelling. As an example, the approach is worked out in detail in conjunction with item response data modelled using the partial credit and generalized partial credit models. Simulation studies are carried out to assess the extent to which the bias caused by ignoring the missing-data mechanism can be reduced. Finally, the feasibility of the procedure is demonstrated using data from a study to calibrate a medical disability scale.

Activities of Daily Living↗

PubMed2004

Practical methods for dealing with 'not applicable' item responses in the AMC Linear Disability Score project.

BACKGROUND: Whenever questionnaires are used to collect data on constructs, such as functional status or health related quality of life, it is unlikely that all respondents will respond to all items. This paper examines ways of dealing with responses in a 'not applicable' category to items included in the AMC Linear Disability Score (ALDS) project item bank. METHODS: The data examined in this paper come from the responses of 392 respondents to 32 items and form part of the calibration sample for the ALDS item bank. The data are analysed using the one-parameter logistic item response theory model. The four practical strategies for dealing with this type of response are: cold deck imputation; hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. RESULTS: The item and respondent population parameter estimates were very similar for the strategies involving hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. The estimates obtained using the cold deck imputation method were substantially different. CONCLUSIONS: The cold deck imputation method was not considered suitable for use in the ALDS item bank. The other three methods described can be usefully implemented in the ALDS item bank, depending on the purpose of the data analysis to be carried out. These three methods may be useful for other data sets examining similar constructs, when item response theory based methods are used.

Activities of Daily Living↗

PubMed2003

Power analysis in randomized clinical trials based on item response theory.

Patient relevant outcomes, measured using questionnaires, are becoming increasingly popular endpoints in randomized clinical trials (RCTs). Recently, interest in the use of item response theory (IRT) to analyze the responses to such questionnaires has increased. In this paper, we used a simulation study to examine the small sample behavior of a test statistic designed to examine the difference in average latent trait level between two groups when the two-parameter logistic IRT model for binary data is used. The simulation study was extended to examine the relationship between the number of patients required in each arm of an RCT, the number of items used to assess them, and the power to detect minimal, moderate, and substantial treatment effects. The results show that the number of patients required in each arm of an RCT varies with the number of items used to assess the patients. However, as long as at least 20 items are used, the number of items barely affects the number of patients required in each arm of an RCT to detect effect sizes of 0.5 and 0.8 with a power of 80%. In addition, the number of items used has more effect on the number of patients required to detect an effect size of 0.2 with a power of 80%. For instance, if only five randomly selected items are used, it is necessary to include 950 patients in each arm, but if 50 items are used, only 450 are required in each arm. These results indicate that if an RCT is to be designed to detect small effects, it is inadvisable to use very short instruments analyzed using IRT. Finally, the SF-36, SF-12, and SF-8 instruments were considered in the same framework. Since these instruments consist of items scored in more than two categories, slightly different results were obtained.

Health Status↗

PubMed2003

Evaluation of global testing procedures for item fit to the Rasch model.

Two types of global testing procedures for item fit to the Rasch model were evaluated using simulation studies. The first type incorporates three tests based on first-order statistics: van den Wollenberg's Q(1) test, Glas's R(1) test, and Andersen's LR test. The second type incorporates three tests based on second-order statistics: van den Wollenberg's Q(2) test, Glas's R(2) test, and a non-parametric test proposed by Ponocny. The Type I error rates and the power against the violation of parallel item response curves, unidimensionality and local independence were analysed in relation to sample size and test length. In general, the outcomes indicate a satisfactory performance of all tests, except the Q(2) test which exhibits an inflated Type I error rate. Further, it was found that both types of tests have power against all three types of model violation. A possible explanation is the interdependencies among the assumptions underlying the model.

Aptitude Tests↗