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  • 1. Anwar, Muhammad Ikram
    et al.
    Rahman, Moazur
    Ul Hassan, Mahmood
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Iqbal, Mazhar
    Prevalence of active hepatitis C virus infections among general public of Lahore, Pakistan2013In: Virology Journal, ISSN 1743-422X, E-ISSN 1743-422X, Vol. 10, article id 351Article in journal (Refereed)
    Abstract [en]

    Background: To find out the prevalence of active hepatitis C virus (HCV) infections among general public in Lahore city, since data concerning the prevalence of active HCV in this city is currently unavailable. Methods: Blood samples were collected randomly from individuals visiting different clinical laboratories in Lahore. Serum was separated and processed by nested PCR qualitative assay for the detection of HCV RNA. The samples were categorized into different age groups on the basis of pre-test questionnaires in order to record the age-wise differences regarding the prevalence of active HCV. Data were analyzed statistically using Chi-Square test. Results: Out of the 4246 blood samples analyzed in this study, 210 were confirmed to be positive for active HCV infection. Gender-wise active HCV prevalence revealed no significant difference [OR = 1.10 CI = (0.83-1.46), p > 0.05]. However, among the age groups the highest prevalence was observed in the age groups 20-29 (7.7%) and 30-39 years (6.4%) with odds of prevalence of 14.8% (OR = 2.48, CI = (1.40-4.38), p < 0.05) and 10.3% (OR = 2.03, CI = (1.10-3.71), respectively. In age groups above 40 years (40-49, 50-59 and >59 years), a decrease in levels of active HCV prevalence was observed. Conclusions: Among tested samples, 4.9% of the subjects were confirmed to harbour active HCV infections and the middle aged population in Lahore was found to be at a higher risk of the HCV ailments compared to both their younger and older peers.

  • 2.
    Hossain, Md Shakhawat
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Ul Hassan, Mahmood
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Nobi, Mohammad Nur
    Rokonuzzaman, Md
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    The impact of stock market development and banks on economic growth for SAARC countries: a panel analysis2012In: Asian Journal of Research in Business Economics and Management, ISSN 2249-7307, Vol. 2, no 9, p. 49-60Article in journal (Refereed)
    Abstract [en]

    The aim of this study is to determine the effect of stock market development and banks on the economic growth in SAARC countries. A random effect panel model is fitted and it fits the data well. It is observed that market capitalization and domestic credit to private sector have significant positive contribution to the economic growth (GDP) for the sampled SAARC countries whereas domestic credit to banking sector has negative contribution.

  • 3.
    Ul Hassan, Mahmood
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Miller, Frank
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    An exchange algorithm for optimal calibration of  items in computerized achievement testsManuscript (preprint) (Other academic)
    Abstract [en]

    The importance of large scale achievement tests, like national tests in school, eligibility tests for university, or international assessments for evaluation of students, is increasing. Pretesting of questions for the above mentioned tests is done to determine characteristic properties of the questions by adding them to an ordinary achievement test. If computerized tests are used, it has been shown using optimal experimental design methods that it is efficient to assign pretest questions to examinees based on their abilities. We can consider the specific distribution of abilities of the available examinees and apply restricted optimal designs.A previously used algorithm optimizes the criterion directly. We develop here a new algorithm which builds on an equivalence theorem. It discretizises the design space with the possibility to change the grid during the run, makes use of an exchange idea and filters computed designs. We illustrate how the algorithm works in some examples and how convergence can be checked. We show that this new algorithm can be used flexibly even if different models are assumed for different questions.

  • 4.
    Ul Hassan, Mahmood
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Miller, Frank
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Discrimination with Unidimensional and Multidimensional Item Response Theory Models for Educational DataManuscript (preprint) (Other academic)
    Abstract [en]

    Achievement tests are used to characterize the proficiency of higher-education students. Item response theory (IRT) models are applied to these tests to estimate the ability of students (as latent variable in the model). In order for quality IRT parameters to be estimated, especially ability parameters, it is important that the appropriate number of dimensions is identified. Through a case study, based on a statistics exam for  students in higher education, we show how dimensions and other model parameters can be chosen in a real situation. Our model choice is based both on empirical and on background knowledge of the test. We investigate whether dimensionality influences the estimates of the item-parameters, especially the discrimination parameter which provides information about the quality of the item. We perform a simulation study to generalize our conclusions. Both the simulation study and the case study show that multidimensional models have the advantage to better discriminate between examinees.

  • 5.
    Ul Hassan, Mahmood
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Miller, Frank
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Optimal calibration of  items for multidimensional achievement testsManuscript (preprint) (Other academic)
    Abstract [en]

    Multidimensional achievement tests are recently gaining more importance in educational and psychological measurements due to  diagnostic nature. Diagnostic pretests help the organization to assist the students in determining which ability needs to be improved from particular domain of knowledge for better performance in the test. To develop diagnostic pretest items for multidimensional achievement tests, we generalize the previously developed exchange algorithm in multidimensional setting. We also develop an asymptotic theorem which helps us to choose an item at extreme ability levels to sample the examinees.

  • 6.
    Ul Hassan, Mahmood
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Miller, Frank
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Optimal Item Calibration for Computerized Achievement Tests2019In: Psychometrika, ISSN 0033-3123, E-ISSN 1860-0980Article in journal (Refereed)
    Abstract [en]

    Item calibration is a technique to estimate characteristics of questions (called items) for achievement tests. In computerized tests, item calibration is an important tool for maintaining, updating and developing new items for an item bank. To efficiently sample examinees with specific ability levels for this calibration, we use optimal design theory assuming that the probability to answer correctly follows an item response model. Locally optimal unrestricted designs have usually a few design points for ability. In practice, it is hard to sample examinees from a population with these specific ability levels due to unavailability or limited availability of examinees. To counter this problem, we use the concept of optimal restricted designs and show that this concept naturally fits to item calibration. We prove an equivalence theorem needed to verify optimality of a design. Locally optimal restricted designs provide intervals of ability levels for optimal calibration of an item. When assuming a two-parameter logistic model, several scenarios with D-optimal restricted designs are presented for calibration of a single item and simultaneous calibration of several items. These scenarios show that the naive way to sample examinees around unrestricted design points is not optimal.

  • 7.
    Ul Hassan, Mahmood
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Stockhammar, Pär
    Stockholm University, Faculty of Social Sciences, Department of Statistics.
    Fitting probability distributions to economic growth: a maximum likelihood approach2016In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 43, no 9, p. 1583-1603Article in journal (Refereed)
    Abstract [en]

    The growth rate of the gross domestic product (GDP) usually carries heteroscedasticity, asymmetry and fat-tails. In this study three important and significantly heteroscedastic GDP series are examined. A Normal, normal-mixture, normal-asymmetric Laplace distribution and a Student's t-Asymmetric Laplace (TAL) distribution mixture are considered for distributional fit comparison of GDP growth series after removing heteroscedasticity. The parameters of the distributions have been estimated using maximum likelihood method. Based on the results of different accuracy measures, goodness-of-fit tests and plots, we find out that in the case of asymmetric, heteroscedastic and highly leptokurtic data the TAL-distribution fits better than the alternatives. In the case of asymmetric, heteroscedastic but less leptokurtic data the NM fit is superior. Furthermore, a simulation study has been carried out to obtain standard errors for the estimated parameters. The results of this study might be used in e.g. density forecasting of GDP growth series or to compare different economies.

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