Quantitative Analysis of Original Data
In short: Collecting and analyzing your own original data is probably the most impressive credential you can take from this program, but it requires focus, advanced planning, and the approval of TC’s Institutional Review Board (IRB) for research with human subjects.
Key Components
- Literature review
- Research question
- Valid instruments & measures
- IRB approval
- Proper sample size
- Data collection
- Statistical tests
- Results & Discussion
The whole story: A quantitative analysis of original data involves collecting, processing, and statistically analyzing numerical data (e.g., surveys, experiments) to investigate a clearly-defined and falsifiable research question or hypothesis.
Students conducting a quantitative analysis of original data must begin with an appropriately comprehensive review of existing empirical literature on their chosen topic, which should describe gaps in the literature and/or future directions still needed. This initial literature review should be written in a manner that serves to justify the value of the current study, either as a valuable addition to the existing empirical knowledge base or as data that could potentially inform future targets for clinical intervention.
Following this, the student must next pose a specific, testable set of questions or hypotheses. A high-quality quantitative research question investigates whether a meaningful relationship exists between a narrow set of clearly defined variables that can be operationally measured using standardized methods such as Likert-type questionnaires, behavioral observations, or experimental tasks.
To this end, the student should next identify research instruments (e.g., scales, tests, experiments, etc.) that are documented as having adequate reliability and validity and are capable of measuring the concepts required to answer the research questions. Where necessary, a limited number of modified scales and novel research instruments designed by the student may be part of the set of research instruments used (e.g., one or two).
The student must next submit an IRB protocol that describes their study, their approach to collecting and handling data, and otherwise demonstrates appropriate management of any potential risks of study participation to ensure ethical standards are met. It is expected that students will design their proposed study in the lowest risk manner possible to feasibly answer their research questions.
Next, the student must collect and handle data adhering fully to the methods described in their IRB protocol. The resulting dataset should have a sample size large and robust enough to support meaningful statistical analysis, but this can include smaller sizes that would qualify as a “pilot study.” Power analysis should be used to aid in identifying a minimally-viable sample size (e.g., using G*Power or a similar software tool).
Statistical techniques used must suit the data and question, and quantitative statistical software, such as SPSS or R software, should be used to conduct inferential statistical analyses in a rigorous manner. The student must check assumptions (e.g., normally distributed or skewed data) and explain all statistical choices made and steps taken. Results must be clearly explained and linked back to the research question. Discussion should provide a nuanced account of how results add to the existing empirical knowledge base or inform future targets for clinical intervention, or otherwise add value to the field of clinical psychology. Limitations should be acknowledged and possible future directions for follow-up research should be described. The final integrative project should follow a clear structure (e.g., abstract, introduction, methods, results, discussion, references) and provide well-organized tables or figures as applicable. All references should be properly listed and all writing should be in APA style.
To learn more: APA’s Journal Article Standards for Quantitative Research (https://apastyle.apa.org/jars/quantitative), including a detailed and useful outline (https://apastyle.apa.org/jars/quant-table-1.pdf)
Relevant Courses at TC:
- Research Methods in Clinical Psychology (CCPX)
- Advanced Research Methods in Clinical Psychology (CCPX)
- Programing for Psych Research (CCPX)
- Any of the many Statistics courses offered by HUDK
Please see our Research Methods Concentration for a full list of courses