Browsing by Subject "Analysis"

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    Analyzing Topical Structure in ESL Essays: Not All Topics are Equal
    (Copyright © Cambridge University Press [BREAK]The original doi for the as-published version of the article is 10.1017/S0272263100009517. To access the doi, open the following DOI site in your browser and cut and paste the doi name where indicated: [LINK]http://dx.doi.org[/LINK][BREAK]Access to the original article may require subscription and authorized logon ID/password. IUPUI faculty/staff/students please check University Library resources before purchasing an article. Questions on finding the original article via our databases? Ask a librarian: [LINK]http://www.ulib.iupui.edu/research/askalibrarian[/LINK]., 1990) Schneider, Melanie; Connor, Ulla, 1948-
    Topical structure analysis (TSA), a text-based approach to the study of topic in discourse, has been useful in identifying text-based features of coherence. It has also been used to distinguish between essays written by groups of native English speakers with varying degrees of writing proficiency (Witte, 1983a, 1983b). More recently, TSA has distinguished between higher and lower rated ESL essays, but with different results from those found with native speakers of English (Connor & Schneider, 1988). The present study replicated the previous ESL study of two groups of essays written for the TOEFL Test of Written English with three groups of essays. Findings indicate that two topical structure variables, proportions of sequential and parallel topics in the essays, differentiate the highest rated group from the two lower rated groups. We offer explanations for the results and propose that all occurrences of a particular type of topic progression do not contribute equally to the coherence of a text.
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    Research methods in genetic counseling: Statistical approaches and resources
    (Wiley, 2025) Helm, Benjamin M.; Wetherill, Leah; Medical and Molecular Genetics, School of Medicine
    The continuing evolution of the genetic counseling profession necessitates an ongoing reflection on the perceived validity and role of our research in the larger systems we operate in. Despite our need for an analytically inclined professional culture and decision-making process, many genetic counselors may not have the training or support needed to ensure such rigor. In this special issue of the Journal of Genetic Counseling, authors were tasked with providing methodological foundations for genetic counselors navigating various phases of research, to improve the quality of our research output and to incorporate our findings into decision-making in healthcare and non-healthcare settings. In this manuscript, we describe various statistical approaches in lay terms and provide resources for genetic counselors new and seasoned alike. We hope to ease some of the trepidation in applying statistical approaches to genetic counseling research and provide resources to increase the analytical confidence of our workforce. This can increase the validity of the analyses and findings disseminated within and beyond our profession. First, we review some history and foundations of statistical practices that inform study design, sampling, data collection, analysis, and interpretation. Next, we highlight how different study designs inform the choice of data analysis and provide resources for statistical strategy choice. Finally, we provide resources on how to interpret statistical test results, recommend best practices, and highlight common but avoidable misconceptions in statistical interpretation. We hope this review provides a framework for novices in quantitative methodology and provides the language needed to collaborate with analytical/statistical colleagues.