Module 8 Flashcards
(49 cards)
Descriptive epidemiology
Describes characteristics of a population
- Health needs
- Health events
- Health outcomes
Inferential epidemiology
Compares two or more populations for differences or similarities
Sampling
Done when data can’t be collected from entire population
- Subset of population provides estimate
- Sample is drawn from a sampling frame or list of those available to be sampled (ex: phone book)
Sampling methods
- Convenience sample
- Probability sample
- Systematic sampling
- Stratified random sampling
Convenience sample
Nonrandom selection, e.g., first 50 to enter clinic
Probability sample
- Uses some random mechanism to draw sample from sampling frame
- Each member in sample equally as likely to be chosen
Systematic sampling
e.g., Randomly choose one of first 20 patient charts, then every 20th chart thereafter to get a 5 percent sample
Stratified random sampling
Stratify sample into categories (e.g., age within gender) and then randomly sample from within each category
Statistical measures of effect
- Significance tests
- The p value
- Confidence Interval
Levels of measurement: 2 classes of data
- Continuous
2. Categorical
Continuous variable
- Distance between points meaningful
- Variable can take any value between points
- Age, height, weight, blood pressure
Categorical variable
Take values in fixed number of categories
- Ordinal—categories can be ordered in some way (ex: patient satisfaction —from not satisfied to very satisfied)
- Nominal—categories are “qualitative” (race, gender)
Descriptive statistics for continuous variables
- Measures of central tendency
2. Measures of dispersion/variation
Measures of central tendency
- Mean: average value
2. Median: half observation below, half above
Measures of dispersion/variation
- Standard deviation: average distance that variables fall
from the mean - Variance: square of standard deviation
- Range: distance from lowest to highest value
Descriptive statistics for categorical variables
- Frequency distribution presented graphically
- Proportion: number with attribute/total #
- Rate: a proportion multiplied by some number
Inferential statistics
Compare two or more samples for some characteristic
Tests specific hypotheses regarding populations
-Two-sided hypothesis: makes no assumptions regarding which population has the higher (or lower) value
-One-sided hypothesis: assumes one population has a higher or lower value
p Value
Probability of observed differences being due to random chance
- Statistically significant: p
Null hypothesis
States that there is no difference among the groups being compared
*Underlying all statistical tests is a null hypothesis
Significance tests
Used to decide whether to reject or fail to reject a null hypothesis
Significance level
Chance of rejecting the bull hypothesis when it is actually true
Confidence intervals
The test statistic +/- some quantity An alternative to the hypothesis test Provides a range in which the true value will probably lie Depend on: -Variability: (higher > larger CI) -Sample size: smaller > larger CI)
Statistical power
Ability of a study to demonstrate an association if one exists; probability that we will correctly determine that the null is false and reject it
Determined by:
-Frequency of the condition under study – Magnitude of the effect
-Study design
-Sample size
Two-sample T test
Compare mean values of a continuous value from 2 groups Need to know: -Mean of each group -Size of each group -Variance for each group