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Formulating Research Questions using Backward Approach in Statistics

Learn how to formulate a research question using a backwards approach in statistics. Understand problem identification, knowledge gap, previous findings, and hypothesis development. Discover how to analyze data and determine required sample size.

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Formulating Research Questions using Backward Approach in Statistics

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  1. Formulation of a researchUsing Backward approach Bandit Thinkhamrop, PhD.(Statistics) Dept. of Biostatistics & Demography Faculty of Public Health Khon Kaen University

  2. Formulating a research question • Use a funnel type of logical • Outline what is the problem, what has been known and unknown, identifying knowledge gap, address a question of the study: • The nature and scope of the problem • Previous findings • The gap of the knowledge • The research question (hypothesis) Source: https://www.ctnbestpractices.org/edu/crwseries/

  3. Core QuestionsBegin at the destination • What is the research question? • What is the expected answer or the conclusion? • What is the expected magnitude of effect to be used as the basis of the conclusion? • What is the implication of the findings? • What could influence the validity of the data and how to avoid them? • How to analyze the data to get the targeted magnitude of effect? • What is the required sample size?

  4. 1. What is the research question? • State the research question • If more than one questions, select one to be the primary research question • Example: • What are predictors of low birth weight? • What is the efficacy of the HIV vaccine?

  5. 2. What is the answer or the conclusion? • State the expected the answer to the primary research question • Example: • Low BMI of mother and not received ANC increase risk of low birth weight • HIV vaccine can prevent HIV infection

  6. 3. What is the expected magnitude of effect to be used as the basis of the conclusion? • Specify type of the primary outcome variable • Specify type of the magnitude of effect: • Absolute effect (mean or mean difference, proportion or proportion difference, rate, correlation coefficient, kappa, etc.) • Relative effect (relative risk, odds ratio, incidence rate ratio, or hazard ratio) • Specify its expected magnitude to be determine and the minimum magnitude that is meaningful

  7. 4. What is the implication of the finding? • Specify benefits of the finding • State an expected recommendation

  8. 5. What could influence the validity of the data and how to avoid them? • Describe briefly how the magnitude of effect would be obtained • Describe how it could be wrong by considering these sources of biases: • Selection bias • Information bias • Confounding bias • Describe how to avoid, prevent, or minimize them

  9. 6. How to analyze the data to get the targeted magnitude of effect? • Select statistical methods based on type of the primary outcome and the study design • Describe how to analyze the data, focusing on the primary research question • Construct key dummy tablesfor presentation of the results

  10. 7. What is the required sample size? • Stick to the primary outcome • Identify and review the magnitude of effect and its variability that will be used as the basis of the conclusion of the research. • Identify what statistical method that will be used to obtain the main magnitude of effect. • Calculate the sample size • Evaluate if this sample size would provide a precise and conclusive answer to the research question by analyze the data as if it is as expected. • Describe how the sample size is calculated with sufficient details that allow explicability.

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