Validity of using item response theory to analyze data from the Work Limitations Questionnaire

The Work Limitations Questionnaire (WLQ) is used to determine the amount of work loss and productivity which stem from certain health conditions, including rheumatoid arthritis and cancer. The questionnaire is currently scored using methodology from Classical Test Theory. Item Response Theory, on the other hand, is a theory based on analyzing item responses. This study wanted to determine the validity of using Item Response Theory (IRT), to analyze data from the WLQ. Item responses from 572 employed adults with dysthymia, major depressive disorder (MDD), double depressive disorder (both dysthymia and MDD), rheumatoid arthritis and healthy individuals were used to determine the validity of IRT (Adler et al., 2006).^ PARSCALE, which is IRT software from Scientific Software International, Inc., was used to calculate estimates of the work limitations based on item responses from the WLQ. These estimates, also known as ability estimates, were then correlated with the raw score estimates calculated from the sum of all the items responses. Concurrent validity, which claims a measurement is valid if the correlation between the new measurement and the valid measurement is greater or equal to .90, was used to determine the validity of IRT methodology for the WLQ. Ability estimates from IRT were found to be somewhat highly correlated with the raw scores from the WLQ (above .80). However, the only subscale which had a high enough correlation for IRT to be considered valid was the time management subscale (r = .90). All other subscales, mental/interpersonal, physical, and output, did not produce valid IRT ability estimates.^ An explanation for these lower than expected correlations can be explained by the outliers found in the sample. Also, acquiescent responding (AR) bias, which is caused by the tendency for people to respond the same way to every question on a questionnaire, and the multidimensionality of the questionnaire (the WLQ is composed of four dimensions and thus four different latent variables) probably had a major impact on the IRT estimates. Furthermore, it is possible that the mental/interpersonal dimension violated the monotonocity assumption of IRT causing PARSCALE to fail to run for these estimates. The monotonicity assumption needs to be checked for the mental/interpersonal dimension. Furthermore, the use of multidimensional IRT methods would most likely remove the AR bias and increase the validity of using IRT to analyze data from the WLQ.^

Cataract surgery in cancer patients and its impact on quality of life as measured by the National Eye Institute Visual Functioning Questionnaire - 25 (NEI-VFQ-25)

Purpose. The measurement of quality of life has become an important topic in healthcare and in the allocation of limited healthcare resources. Improving the quality of life (QOL) in cancer patients is paramount. Cataract removal and lens implantation appears to improve patient well-being of cancer patients, though a formal measurement has never been published in the US literature. In this current study, National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25), a validated vision quality of life metric, was used to study the change in vision-related quality of life in cancer patients who underwent cataract extraction with intraocular lens implantation. ^ Methods. Under an IRB approved protocol, cancer patients who underwent cataract surgery with intraocular lens implantation (by a single surgeon) from December 2008 to March 2011, and who had completed a pre- and postoperative NEI-VFQ-25 were retrospectively reviewed. Post-operative data was collected at their routine 4-6 week post-op visit. Patients' demographics, cancer history, their pre and postoperative ocular examinations, visual acuities, and NEI-VFQ-25 with twelve components were included in the evaluation. The responses were evaluated using the Student t test, Spearman correlation and Wilcoxon signed rank test. ^ Results. 63 cases of cataract surgery (from 54 patients) from the MD Anderson Cancer Center were included in the study. Cancer patients had a significant improvement in the visual acuity (P<0.0001) postoperatively, along with a significant increase in vision-related quality of life (P<0.0001). Patients also had a statistically significant improvement in ten of the twelve subcategories which are addressed in the NEI-VFQ-25. ^ Conclusions. In our study, cataract extraction and intraocular implantation showed a significant impact on the vision-related quality of life in cancer patients. Although this study includes a small sample size, it serves as a positive pilot study to evaluate and quantify the impact of a surgical intervention on QOL in cancer patients and may help to design a larger study to measure vision related QOL per dollar spent for health care cost in cancer patients.^

The business management strategy of Iran's large apparel firms : overview of results from a questionnaire survey and interviews 2009-2011

This paper is an overview of the results from a questionnaire survey and subsequent supplementary interviews of Iran's large apparel firms conducted by the author in 2009-2011. Most of the large apparel firms in Iran are based in Tehran and have been in business for some twenty years. They have a solid business with regular customers, but in general have hesitated to expand the size of their firms. Following the relaxation of restrictions on the procurement of raw materials that existed in the 1990s, the results of survey and interviews show that the firms have developed new channels of procurement although they depend to a considerable degree on imported raw materials and machinery. They have managed to maintain their level of output even with the rapid increase in imports since 2000, although the number of firms has decreased. Low-priced Chinese products have basically not been their rivals; instead, the inflow of foreign name-brand products have hit them heavily.

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

Assessment of the requirement management process using a two-stage questionnaire

This research advocates the idea that although requirements management process is not carried out in many organizations there is some people within the organization that perform some requirements management practices. However, these practices are usually not documented and as consequence are not spread across the organization. This paper proposes an assessment methodology based on a two-stage questionnaire to identify which practices of the requirements management process are performed but not documented, which practices require to be prioritized and which are not implemented due to bad management or unawareness. In order to validate the assessment methodology, the questionnaire was applied to an industrial case study.

Determining practices achievement in the requirement management process using a two-stage questionnaire

This paper aims to obtain a baseline snapshot of the requirement management process using a two-stage questionnaire to identify both performed and non-performed CMMI practices. The questionnaire proposed in this paper may help with the assessment of the requirement management process, provide useful information related to the current state of the process, and indicate those practices that require immediate attention with the aim of begin a Software Process Improvement program.

Diseño y validación de un cuestionario socio-emocional para jóvenes futbolistas de élite. Desing and validation of a socio-emotional questionnaire for yourh footbal players

Validación de un cuestionario socio-emocional en fútbol

Predicting EQ-5D from the Parkinson's disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect