Comprehensive Study Guide for Quiz 1: Study Designs, RCTs, Bias - PDF
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This study guide provides a detailed overview of various study designs including experimental, and observational studies like cross-sectional, cohort, and case-control. It explores randomized controlled trials (RCTs), measures of disease frequency, and key biases like selection and information bias, while also examining statistical tests and study design applications. This document is useful for anyone preparing for an exam with questions on epidemiology.
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Class notes **Comprehensive Study Guide for Quiz 1** **I. Study Designs** **1. Experimental Studies** - Investigator **manipulates the intervention** and controls its distribution. - Used to establish **causality**. **2. Observational Studies** - **No intervention manipulation**. -...
Class notes **Comprehensive Study Guide for Quiz 1** **I. Study Designs** **1. Experimental Studies** - Investigator **manipulates the intervention** and controls its distribution. - Used to establish **causality**. **2. Observational Studies** - **No intervention manipulation**. - Investigator observes exposures and outcomes. - Types: - **Cross-Sectional Study** -- Snapshot of exposure and outcome at a single point in time. - **Cohort Study** -- Follows a group over time to see who develops the outcome. - **Case-Control Study** -- Compares people with and without a disease to find past exposures. - **Ecological Study** -- Uses **group-level data** instead of individual data. **3. Key Study Design Differences** - **RCT vs. Quasi-Experimental:** RCTs use **randomization**, quasi-experimental studies do not. - **Cross-Sectional vs. Cohort:** Cross-sectional studies assess prevalence at one time, while cohort studies follow participants over time. - **Cohort vs. Case-Control:** Cohort studies start with exposure and follow forward, case-control studies start with outcome and look back. **II. Randomized Controlled Trials (RCTs)** **1. Importance of Randomization** - **Eliminates selection bias**. - **Controls for confounders** (both known and unknown). - Ensures **valid statistical comparisons**. **2. Types of Randomization** - **Simple Randomization** -- Like flipping a coin. - **Blocked Randomization** -- Ensures equal group sizes. - **Stratified Randomization** -- Balances key variables (e.g., age, disease severity). **3. Control Groups in RCTs** - **Placebo Control** -- Inactive substance. - **Active Control** -- Existing treatment. - **Delayed Intervention** -- Control gets treatment later. - **Usual Care Control** -- Standard treatment used in clinical practice. **4. Allocation Concealment vs. Blinding** - **Allocation Concealment:** - Prevents selection bias before randomization. - Ensures **researchers can't influence group assignment**. - Example: Sealed opaque envelopes, computer-generated randomization. - **Blinding (Masking):** - Prevents bias after randomization. - **Types:** - **Single-blind:** Only participants are unaware. - **Double-blind:** Participants & researchers are unaware. - **Triple-blind:** Participants, researchers, and analysts are unaware. - **Not always feasible** (e.g., surgery trials). **III. Measures of Disease Frequency** **1. Prevalence** - **Measures existing cases** at a point in time. - **Types:** - **Point Prevalence** = Snapshot of disease at a specific time. - **Period Prevalence** = Cases over a set period. **2. Incidence** - **Measures new cases over time**. - **Types:** - **Cumulative Incidence (Risk):** - Formula: **New cases / Population at risk**. - **Incidence Rate (Incidence Density):** - Formula: **New cases / Total person-time at risk**. **IV. Measures of Association** **1. Risk Ratio (Relative Risk, RR)** - Used in **cohort studies**. - Formula: **Risk in exposed / Risk in unexposed**. - Interpretation: RR \> 1 = Exposure increases risk; RR \< 1 = Exposure decreases risk. **2. Odds Ratio (OR)** - Used in **case-control studies**. - Formula: **(a × d) / (b × c)** (from a 2x2 table). - Interpretation: OR \> 1 = Higher odds of disease in exposed group. **3. Prevalence Proportion Ratio (PPR) & Prevalence Odds Ratio (POR)** - Used in **cross-sectional studies**. - **PPR Formula:** Prevalence in exposed / Prevalence in unexposed. - **POR Formula:** **(a × d) / (b × c)**. - **Used when prevalence is high**. **V. Bias and Limitations** **1. Key Biases in Studies** - **Selection Bias:** Due to improper participant selection. - **Information Bias:** Errors in measuring exposure or outcome. - **Confounding:** When another factor influences the relationship. - **Survivor Bias (Incidence-Prevalence Bias):** Disease cases that die quickly may not be captured in cross-sectional studies. **2. Ecological Fallacy** - Occurs in **ecological studies**. - Applying **group-level associations** to individuals incorrectly. - Example: Cities with high ice cream sales have higher drowning rates (confounder: hot weather). **VI. Choosing the Right Statistical Test** **1. Comparing Proportions (Categorical Data)** - **Chi-Square Test** -- Compares **percentages or frequencies** in two or more groups. **2. Comparing Means (Continuous Data)** - **t-Test** -- Compares **means between two groups**. - **ANOVA** -- Compares **means across three or more groups**. **3. Regression Analysis** - Used to measure the effect of multiple variables on an outcome. **VII. Study Design Applications** **1. When to Use Each Study Type** - **RCTs:** When testing a new intervention. - **Cohort Studies:** When studying risk factors over time. - **Case-Control Studies:** When disease is rare and you want to look back at exposures. - **Cross-Sectional Studies:** When estimating disease prevalence. - **Ecological Studies:** When using group-level data for comparisons. This guide covers all necessary content for your quiz. Use it for focused studying!
