Prospective Epidemiological Studies: Risk & Incidence
Prospective Epidemiological Studies
Prospective (Follow-Up) Study:
- A type of cohort study which analyzes risk factors and follows a group of people who do not have the disease, using correlations to determine the absolute risk of subject contraction.
- Prospective = cause → effect
- Cohort = group of people who share a common characteristic or experience within a defined period (e.g., are born, are exposed to a drug or vaccine or pollutant, or undergo a certain medical procedure).
- Two groups of patients
Statistical Inference: Sampling, Bootstrapping, and Confidence Intervals
Packages: Infer (sampling), ggplot2 for visualization, tidyr for data manipulation (part of tidyverse), dplyr for data wrangling, and readr for spreadsheet data.
Sampling Techniques
Sampling: Use rep_sample_n for random draws from a population, ensuring unbiased samples. As replicates increase, the sampling distribution becomes more symmetric and bell-shaped. As sample size (n) increases, variability (SD) for the sampling distribution decreases.
Population Terminology
Population Terminology:
- Population:
Hypothesis Formulation in Research: Types and Uses
Hypothesis Formulation
Scenarios show us what we are looking for or trying to prove and can be defined as tentative explanations of the phenomenon under investigation, made by way of propositions. A variable is a property that may vary (to acquire different values) and whose variation is susceptible to measurement.
Research: Hypotheses, Questions, and Objectives
Assumptions commonly arise from the objectives and research questions.
Origin of Hypotheses
Our hypotheses can arise from a postulate of a theory,
Read MoreCorrelation, Probability, and Hypothesis Testing
Understanding Correlation and Its Applications
1. Types of Correlations:
- Positive: Both variables move in the same direction.
- Negative: Variables move in opposite directions.
- Zero: No relationship between the two variables.
2. Scatterplots: Visual representations of the relationship between two variables.
3. Correlation Scale: Ranges from -1 to 0 (negative correlation) and from 0 to +1 (positive correlation).
4. Formulas: Include formulas for covariance and the correlation coefficient in your cheat sheet.
Read MoreUnderstanding Exponents, Divisibility, and Fractions
Understanding Exponents
Exponentiation is a multiplication of equal factors. For example: 2.2.2.2.2 = 25 (where 5 is the exponent and 2 is the base). The base indicates how many times it is multiplied by itself.
- 43 = 4.4.4 = 64
- 8.8.8.8.8 = 85
- Base 2, exponent 6 = 64
- Base 0, exponent 9 = 0
Order of operations with exponents:
- Powers
- Multiplications
- Additions and subtractions
For example: 3.24 + 25 = 3.16 (= 24) + 32 (= 25) = 48 + 32 = 80.
Properties of Exponentiation
- Multiplication of powers with the same base:
Statistics and ggplot2: Quick Reference
Statistics and ggplot2: Quick Reference
Central Tendency
- Mean: The average of values, affected by outliers.
- Formula: \(\bar{x} = \frac{\Sigma x_i}{n}\)
- Median: The middle value, robust to outliers.
- Mode: The most frequent value in a dataset.
Variability Metrics
- Range: \(\text{Max} – \text{Min}\)
- Population Variance: \(\sigma^2 = \frac{\Sigma (x_i – \mu)^2}{N}\)
- Sample Variance: \(s^2 = \frac{\Sigma (x_i – \bar{x})^2}{n-1}\) (Bessel’s correction).
- Standard Deviation (SD): The square root of variance.
- Formula: