Original ArticlesMinimizing Variability in Language Sampling Analysis A Practical Way to Calculate Text Length and Time Variability and Measure Reliable Change When Assessing ClientsSpencer, Elizabeth; Bryant, Lucy; Colyvas, KimAuthor Information School of Humanities & Social Science (Dr Spencer) and School of Mathematics & Physical Science (Mr Colyvas), The University of Newcastle, Callaghan, New South Wales, Australia; and University of Technology Sydney, Graduate School of Health, Broadway, Ultimo, New South Wales, Australia (Dr Bryant). Corresponding Author: Elizabeth Spencer, PhD, School of Humanities & Social Science, The University of Newcastle, University Dr, Callaghan, NSW, 2308 Australia (Liz.Spencer@newcastle.edu.au). The research on which this paper is based was conducted as part of the Australian Longitudinal Study on Women's Health by The University of Queensland and The University of Newcastle. The authors are grateful to the Australian Government Department of Health for funding and to the women who provided the survey data. The authors have no conflicts of interest to declare. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.topicsinlanguagedisorders.com). Topics in Language Disorders: April/June 2020 - Volume 40 - Issue 2 - p 166-181 doi: 10.1097/TLD.0000000000000212 Buy SDC Metrics Abstract Variability is common in language sample analysis (LSA), arising from personal factors such as age or level of education, or from factors within the text such as its length and purpose. Variability can affect interpretation of results in clinical practice and research studies, as well as the ability to detect change in individuals over time. This article focuses on sample length and time-based variability in the LSA literature and how it has been addressed through a scoping review. We then propose a method for estimating the effect of this common source of variability to allow determination of reliable change in individuals over time. Although some sources of variability are acknowledged in the research literature and clinical evidence-based practice, there has been no consistent method to account for these. The proposed method we present offers a means to address text length and time-based variability and materials and examples to facilitate its implementation in future studies and practice. © 2020 Wolters Kluwer Health, Inc. All rights reserved.