Home >> iCAREcommunity >> Evaluation >> Clinical Data Analysis

 

Clinical Data Analysis

Clinical data analysis is an essential component of evaluating progress and outcomes of individuals and groups. The application of statistical/analytical techniques aid in determining whether hypotheses-driven interventions are effective after their implementation. From the analyses, the progress of individuals and groups could be established. This valuable information could then inform immediate or future changes in intervention programmes. Moreover, aside from analysing the effectiveness of interventions, feedback from stakeholders in the form of surveys could also be analszed to gather insights on trainings and programmes. Entry-level psychologists are expected to:

  • Demonstrate basic understanding of quantitative and qualitative data-analysis methods on commonly applied clinical designs such as case study, single subject experiment, small group design, and survey design.

  • Familiar with the basic order of data analysis (i.e. exploratory -> primary analyses -> post-hoc).

  • Select and apply appropriate statistical/analytical techniques to analyze different clinical hypotheses and designs.

  • Ensure data is in the right structure and format (coding the variables) before analysis.

  • Think critically during interpretation results of data, and discern whether clinical hypotheses are supported.

  • Effectively communicate accurate clinical results in a clear and concise manner.

  • Be flexible, meticulous, open-minded when conducting clinical data analyses.

  • Have a Scientist-practitioner mind-set in utilising data to inform interventions and practices.

 

Yin (2012): Pages 15-18 on Case Study analysis

This brief paper touches on the following techniques for analysing case study data:

  • Pattern matching

    • For comparing your empirically based pattern (based on the data you had collected) with a predicted one

  • Explanation building

    • For open-ended research questions

  • Time-series analysis

    • To examine chronological pattern

  • Replication

    • For multiple case studies

Yin, R. K. (2012). A (very) brief refresher on the case study method. Applications of case study research, 3-20.

Access Link: https://www.sagepub.com/sites/default/files/upm-binaries/41407_1.pdf

Field, Shapiro, and Stiles (1994): Pages 399 – 401 on the procedures and methods of Case Study analysis

This article provides a practical means to track a client’s therapy progress over time through:

  • A weekly client-rated questionnaire with statements individualised to the client

  • Monitoring weekly session impact

  • Psychological change (through the assimilation model)

Field, S. D., Barkham, M., Shapiro, D. A., & Stiles, W. B. (1994). Assessment of assimilation in psychotherapy: A quantitative case study of problematic experiences with a significant other. Journal of Counseling Psychology, 41, 397.

Access Link: https://psycnet.apa.org/doiLanding?doi=10.1037%2F0022-0167.41.3.397

Blackstone (2018): Chapter 8, Section 8.5: Analysis of Survey Data. Pages 103 – 107.

This book chapter touches on the following:

  • Data preparation for analyses: calculating response rate; ensuring that data is in analysable numbers

  • Programs commonly used to analyse data: SPSS, MicroCase, Excel

  • Identify patterns in survey data through:

  • Univariate analyses: descriptive statistics such as mean, median, and mode

  • Bivariate analyses: relationship between 2 variables

  • Cross-tabulation

  • Multivariate analyses: the relationship between 3 or more variables

Blackstone, A. (2018). Principles of sociological inquiry: Qualitative and quantitative methods.

Access Link: https://saylordotorg.github.io/text_principles-of-sociological-inquiry-qualitative-and-quantitative-methods/s11-survey-research-a-quantitative.html

Nonparametric Tests

This resource covers the basic non-parametric tests that can be run to analyse small groups. Non-parametric tests are used when your data is not normal (i.e., distribution of the data). 

Summary of Word Document:

  • Mann Whitney U Test

  • Wilcoxon Signed Ranks Test

  • Chi-square

  • Binomial Sign Test

  • Spearman’s Rho

Summary of video:

  • What is a Nonparametric Test?

  • What are Assumptions in Nonparametric Test?

  • What are the Limitations of the Nonparametric Test?

  • Types of Nonparametric Test and Their selection

  • Action Items for practical learning of Lean Six Sigma

Access Link:

Word document: http://www.ocr.org.uk/Images/260143-inferential-statistics-parametric-and-non-parametric-student-workbook.docx

Video: https://www.youtube.com/watch?v=FiEQz3qIaCk

Meaningful Analysis of Small Data Sets: A Clinician’s Guide

Smaller data sets usually require a slightly different approach.

In this paper, Collins et al. (2017) attempts to properly define techniques to extract meaningful information from small-group data. This paper sheds light on common problems found in analysing small medical data sets using tests such as the T-test, Chi-square test, ANOVA, and non-parametric tests, as well as ways to combat them. 

Access Link: https://hsc.ghs.org/wp-content/uploads/2016/11/GHS-Proc-Finding-Meaning-In-Small-Data-Sets.pdf

Single subject research designs for disability research

Zhan and Ottenbacher (2017): This article provides an overview on single subject designs and how they can be used in various environments as well a review of visual and basic statistical methods used in single subject designs

Summary of resource:

  • Various analysis methods that can be conducted on single-subject data subject data such as:

  • Visual analysis: Target behavior can be understood based on visual representation on a line graph e.g. trend, slope, variability

  • Split middle trend: A step-by-step guide on how to determine a subject’s pattern in performance using the celebration line

  • Running median

  • Randomization tests

Zhan, S., & Ottenbacher, K. J. (2001). Single subject research designs for disability research. Disability and rehabilitation, 23, 1-8.

Access Link: https://www.researchgate.net/profile/Kenneth-Ottenbacher-2/publication/12118674_Single_subject_research_designs_for_disability_research/links/56c6072508ae8cf828fe8966/Single-subject-research-designs-for-disability-research.pdf

Single Subject Design

Engel and Schutt (2019): This chapter provides an in-depth explanation of the basics of conducting visual inspection on single subject data as well as the type of single subject designs.

Summary of resource:

  • Foundations of single subject data

  • Visual analysis

  • Level

  • Trend

  • Variability

Engel, R., & Schutt, R. (2019). The Practice of Research in Social Work (4th ed., p. 307). USA: SAGE.

Access Link: https://www.sagepub.com/sites/default/files/upm-binaries/25657_Chapter7.pdf

Your Survey Closed, Now What? Quantitative Analysis Basics

Summary of resource:

This video covers, in detail, the basic statistical tests used to analyse survey data using SPSS:

  • Bivariate analyses

  • Chi-square test

  • t-test

  • ANOVA