Quantitative Research Proposal:

(Leavy, 2021)

1. Title Template:

   • Use quantitative titles that clearly state the main topic and design approach.

   • Develop the title from keywords about the study.

2. Abstracts:

   • Provide an overview of the study, including the problem, purpose, research questions, methods, population, and main theory.

   • Typically 150–200 words.

   • Write after completing the rest of the research proposal.

3. Keywords:

   • Use singular words or short phrases (5-6).

   • Think about terms for online research on the topic.

4. Topic:

   • State the phenomenon, variables, relationship being tested, pragmatic issues.

   • Include personal/professional interest, access to samples, funding opportunities.

5. Replication Studies:

   • Purposeful repetition of previous research.

   • Two types: direct and conceptual.

   • Low replication rates due to disincentives, bias, and data-sharing deficiencies.

6. Preregistration:

   • Researchers publicly share analysis plans before data collection.

   • Encourages replication, enhances rigor, and reduces bias.

7. Data Sharing:

   • Large datasets often shared; smaller datasets may be lost.

   • No rules for authors to provide data; some journals encourage sharing.

8. Study Replication Considerations:

   • Availability of information, impact on policy, importance of original findings.

   • Consider social/political value, values system, and timeliness.

9. Historical Perspective on Quantitative Research:

   • Positivism: Reality exists independently, measured by the scientific method.

   • Postpositivism: Objective reality, differing from positivism, no absolute truth claims.

10. Research Purpose Statement and Questions/Hypotheses:

    • Briefly state the purpose, variables, population, and theory.

    • Research questions are central, employ directional language.

    • Hypotheses predict variable relationships.

11. Literature Review:

    • Synthesize recent and landmark studies.

    • Focus on primary sources; define variables operationally.

12. Research Plan - Design and Methods:

    • Select methods based on addressing research purpose.

    • Primary designs: experimental research and survey research.

13. Experimental Research:

    • Oldest quantitative research form.

    • Settings: natural, labs, Internet.

    • Types: preexperiments, true experiments, quasi-experiments.

14. Survey Research:

    • Most widely used in social sciences.

    • Special-purpose surveys in education, health care, and social science.

15. Survey Design and Delivery:

    • Questionnaire construction is a detailed process.

    • Consider respondent burden.

    • Delivery options: in-person, online, mail, telephone.

16. Quantitative Sampling:

    • Probability sampling ensures every element in the population has a chance of selection.

    • Determine sample size based on design and generalization goals.

17. Data Analysis:

    • Prepare data, perform "data cleaning."

    • Use descriptive statistics to summarize data.

    • Inferential statistics test hypotheses.

18. Validity and Reliability:

    • Face, content, construct, statistical, ecological validity.

    • Internal and external validity.

    • Interitem, test–retest, interrater reliability.

19. Interpretation and Representation:

    • Visually depict data using tables, graphs.

    • Include implications for future research.

20. Pilot Test and Ethics Statement:

    • Conduct a pilot test for a complete run-through.

    • Ethical considerations include board approvals, informed consent, and efforts to minimize biases.

21. Reference List and Appendices:

    • Include a full reference list.

    • Appendices: Proposed timeline, budget (if applicable), recruitment letter, instruments.