Maryellen McSweeney

Assessing fatigue in persons with cancer: an instrument development and testing study.

Cancer‐related fatigue (CRF) is a highly prevalent, subjective experience of patients with and survivors of cancer. Effective assessment of the attributes of CRF from the patients perspective is essential. The current study developed a measure of CRF from the patients perspective and determined its psychometric properties for patients with cancer undergoing chemotherapy.

A Multivariate Kruskal-Wallis Test with Post Hoc Procedures.

An explicit statement of a statistic which is a nonparametric analogue to one-way MANOVA is presented. The statistic is a multivariate extension of the nonparametric Kruskal-Wallis test (1952). The large sample reference distribution of the test statistic is derived together with a set of computational formulas for the test statistic. In addition two post hoc procedures are developed and compared. The statistic and its post hoc procedures are illustrated with a data example from the behavioral sciences.

Nonparametric Statistics: Use and Nonuse

This paper clarifies the distinctions among parametric, non-parametric, and distribution free statistical tests. The principal circumstances prompting the use of nonparametric procedures, both rank order and qualitative data Techniques, are identified and illustrated. Historical factors and disciplinary orientations affecting the use of nonparametric procedures are discussed. Finally, some conditions which are conducive to the more frequent use of nonparametric statistics are identified.

Analyzing Dichotomous Data from Two Correlated Samples Measured at Two Points in Time

AbstractThis paper presents a user-oriented technique to analyze dichotomous data arising from a double repeated measures 2 × 2 design. The design under consideration occurs most frequently in survey research in which two matched samples of subjects are measured at two points in time on a dichotomous dependent measure. Test statistics are presented that test for change on the dependent measure over time for each sample separately, as well as an interaction test statistic that compares the change rates between the two samples. An extension of the technique to higher order two-dimensional tables is also suggested.

Errors of Misclassification in Neo-Piagetian Research

Errors of misclassification associated with two concept acquisition criteria and their effects on the actual significance level and power of a statistical test for sequential development of these concepts are the focus of this paper. This study provides a link between various mis classification models and subsequent statistical analyses. In addi tion, explicit illustrations of actual significance levels and power val ues are provided for different misclassincation models. A partial corrective for errors of misclassification is suggested and investi gated via Monte Carlo sampling.

Misclassification Errors and Categorical Data Analysis.

Errors of misclassification and their effects on subsequent categorical data analysis are the focus of this paper. The chi-square test for equality of two proportions is examined in the context of errorful categorical data. The effects of such errors on the significance level and power of the test are illustrated. A correction procedure is developed and discussed. The study extends and elaborates upon the existing misclassification literature with a special emphasis on the implications of misclassification errors for educational research with categorical variables.

Quantal Response Techniques for Random Predictor Variables.

The relationship between quantitative predictors and the probability of occurrence of one or more levels of a qualitative criterion can be analyzed by quantal response techniques. This paper presents two quantal response models. The first model treats the predictors as mathematical variables used as a stratification dimension; the second model uses random variables as predictors. Model II estimation techniques are presented for dichotomous and polychotomous criteria and for single and multiple predictors. The estimation techniques are illustrated with examples of the use of MMPI scale scores to predict the diagnostic classification of psychiatric patients and to model the actual diagnostic classifications of judges. These uses of quantal response methodology are contrasted with those of multiple linear regression and discriminant analysis. Many of the dependent variables collected in school settings are qualitative, e.g., the passing or failing of an item, the mastery or non-mastery of a task, the presence or absence of a behavioral trait or skill. When the interest of the researcher is to relate these variables to quantitative variables, quantal response procedures are potentially applicable for such educational data analyses.

Analysis of Categorical Data When Subjects Can Appear in Any Number of Categories.

A common item format frequently encountered on survey questionnaires is the one which asks respondents to check all those categories which are personally applicable. Thus, if there are r categories a subject is free to check none, one, or up to r categories. If the researcher wants to compare c independent groups on their responses to such an item, the usual chi-square test of homogeneity of distributions is inappropriate since subjects can appear in more than one category of the out-come measure. This paper develops and illustrates a new statistic which can compare the response patterns to the item across groups. Post hoc procedures to be used in conjunction with the statistical test are also developed.

An Application of the Qualitative Logistic Response Model for Characterizing Developmental Patterns of Aggression

A method is proposed for modeling developmental data, in general, and, in particular, the developmental relationship between the age of a child and the presence or absence of aggressive (pushing) behavior using a logistic quantal response model. The proposed model was applied to cross-sectional data on 180 first-, second-, and third-grade children from a study by Hapkiewicz (1973). The results tended to support the hypothesized sex differences and the logistic quantal response model was found to fit the data adequately. An interpretation of the parameter estimates provide interesting conclusions concerning the developmental patterns of aggression for both sexes.