Symbolic computation and exact distributions of nonparametric test statistics

We show how to use computer algebra for computing exact distributions on nonparametric statistics. We give several examples of nonparametric statistics with explicit probability generating functions that can be handled this way. In particular, we give a new table of critical values of the Jonckheere-Terpstra test that extends tables known in the literature

Item-score reliability:Estimation and evaluation

In psychology and education, tests are used to measure intelligence and school performance. Test scores are used to make decisions about individuals (who is admitted to a particular school level or a job?) and have impact on people’s lives as well as on schools and organizations. Thus, test scores must be reliable to guarantee that decisions based on test scores are correct. Reliability is the degree to which retesting a person provides the same result. In practice, re-testing the same persons to determine reliability is unrealistic, because memory and other unwanted effects will influence the test result. Estimation of a test score’s reliability therefore is based on the test results of a sample of people who took the test just once. This approach has produced several methods to estimate reliability of the test score. Methods for estimating the reliability of a test score all relate to a test consisting of multiple items (problems to be solved, questions to be answered). However, individual items also must have high reliability, and thus it is important to assess the reliability of a single item, that is, the item-score reliability. So far, items were assessed using indices that address aspects of item quality other than reliability, but methods to assess item-score reliability were hardly available and thus had to be developed and their performance evaluated. This was the topic of this dissertation. In this dissertation, methods for estimating item-score reliability were developed and the usability of these methods was evaluated. First, reliability methods based on test scores were used as a basis for developing methods for estimating item-score reliability. These methods were evaluated in controlled studies using simulated data. Three promising methods resulted. In a second study, these three item-score reliability methods were used to estimate the item-score reliability in several empirical-data sets. The resulting values were compared to values of item indices assessing other aspects of item quality. The relation between the three item-score reliability methods and the other item indices was investigated in a third study using simulated data. In a final study, the usability of item-score reliability for selecting or rejecting items based on their contribution to test-score reliability was investigated. The studies in this dissertation show that item-score reliability methods provide insight into the quality of an item and help to decide whether an item should be included in the test. Also, the relationship between item-score reliability and other aspects of item quality is investigated. Our methods may contribute to the improvement of psychological and educational tests

Estimation of value-at-risk and expected shortfall using copulas

Includes bibliographical references (leaves 76-77)

Estimation of Exposure Distribution Adjusting for Association Between Exposure Level and Detection Limit

In environmental exposure studies, it is common to observe a portion of exposure measurements to fall below experimentally determined detection limits (DLs). The reverse Kaplan–Meier estimator, which mimics the well‐known Kaplan–Meier estimator for right‐censored survival data with the scale reversed, has been recommended for estimating the exposure distribution for the data subject to DLs because it does not require any distributional assumption. However, the reverse Kaplan–Meier estimator requires the independence assumption between the exposure level and DL and can lead to biased results when this assumption is violated. We propose a kernel‐smoothed nonparametric estimator for the exposure distribution without imposing any independence assumption between the exposure level and DL. We show that the proposed estimator is consistent and asymptotically normal. Simulation studies demonstrate that the proposed estimator performs well in practical situations. A colon cancer study is provided for illustration

Use of statistics in recently-published physical education research

The types and frequencies of statistical techniques reported in recently-published physical education research were studied. Also investigated were: (a) complexity of the data that were analyzed, (b) frequency and levels of significance testing, assumption testing, and data transformation, and (c) characteristics of the reporting of statistical analyses. Stratified random sampling with proportional allocation from seven physical education research journals was used to identify a sample of 233 quantitative research reports. Content analyses revealed that a wide variety of statistical techniques were employed in the sample of reports. Descriptive statistics were reported most frequently; a majority of the reports did, however, employ at least one inferential analysis. A £ value of .05 was the most commonly reported alpha level for significance testing, although most studies failed to state a criterion alpha level. Among the inferential studies, 98% reported statistical "significance" of their findings

ORDERED ALTERNATIVES: A MEANS OF IMPROVING POWER

In analysis of variance settings it is often known that if there are any differences among the means, those differences will fall in a particular order. The usual F test used to look for the existence of differences is not sensitive to the particular order. This paper presents two procedures from the nonparametric literature which have sensitivity to the suggested ordering. The analogy is drawn between these procedures and the two-sample t test. The paper concludes with a simulation study which investigates the power properties of the proposed tests and makes comparisons with the F test

The impact of customer order lead time-based decisions on the firm’s ability to make money : case study: build to order manufacturing of electrical equipment and appliances

fi=vertaisarvioitu|en=peerReviewed

Investigation of preference differences and their effects on the secondary education system of Atlanta in 1985

M.S.Stuart J. Deutsc