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  1. Cohort study data analysis:- Define groups: Exposed vs. unexposed (or comparison cohorts) Describe data: Baseline characteristics (means, proportions) Calculate outcomes: Incidence, risk, or rates Compare groups: Risk ratio (RR) or rate ratio Survival analysis if follow-up time varies Adjust for conRead more

    Cohort study data analysis:-

    1. Define groups: Exposed vs. unexposed (or comparison cohorts)

    2. Describe data: Baseline characteristics (means, proportions)

    3. Calculate outcomes: Incidence, risk, or rates

    4. Compare groups:

      • Risk ratio (RR) or rate ratio

      • Survival analysis if follow-up time varies

    5. Adjust for confounders: Use regression (e.g., Cox, Poisson, logistic)

    6. Check assumptions & missing data

    7. Interpret clinically, not just statistically

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  2. Use regression analysis when you want to quantify and test relationships between variables or make predictions. It is not always required. When you should use it You want to see how one or more factors affect an outcome You need to adjust for confounders You want to predict values (e.g., risk, scoreRead more

    Use regression analysis when you want to quantify and test relationships between variables or make predictions. It is not always required.
    When you should use it

    • You want to see how one or more factors affect an outcome
    • You need to adjust for confounders
    • You want to predict values (e.g., risk, scores, trends)
    • You are testing associations or hypotheses, not just describing data
      When it’s not required

      • Your goal is only descriptive (means, percentages, frequencies)
      • You are comparing groups with simple tests (t-test, chi-square, ANOVA)
      • Sample size or data quality is insufficient for reliable modeling
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  3. You should consult a statistician when: Before starting a study: study design, sample size, variables While planning analysis: choosing appropriate tests or models With complex data: multiple variables, missing data, repeated measures When using advanced methods: regression, survival analysis, mixedRead more

    You should consult a statistician when:

    • Before starting a study: study design, sample size, variables
    • While planning analysis: choosing appropriate tests or models
    • With complex data: multiple variables, missing data, repeated measures
    • When using advanced methods: regression, survival analysis, mixed models
    • If results are unclear or conflicting
    • Before publication: to ensure correct analysis and interpretation
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