Multivariable Modeling - Logistic Regression Flashcards

These flashcards cover essential vocabulary and concepts from the Multivariable Modeling - Logistic Regression lecture.

Logistic Regression

A statistical method for estimating the parameters in a logistic regression model, used to model binary outcome variables.

Odds Ratio

A measure of association between an exposure and an outcome, representing the odds of the outcome occurring in the exposed group relative to the unexposed group.

Maximum Likelihood Estimation

A statistical method used to estimate the parameters of a statistical model, maximizing the likelihood function to find the values of parameters that make the observed data most likely.

Confounding

A situation where an observed association between an exposure and an outcome is distorted by the presence of another variable that is related to both.

Descriptive Epidemiology

A type of epidemiologic study focused on describing the distribution of diseases within a population.

Analytic Epidemiology

A type of epidemiologic study aimed at identifying determinants of disease and testing hypotheses about associations.

Indicator Variables

Also known as dummy variables, these are used to represent categorical variables with numerical values for inclusion in regression models.

Confidence Interval

A range of values derived from sample data that is likely to contain the true population parameter, providing an estimate of the precision of the sample statistic.

Wald Test

A statistical test used to assess the significance of individual coefficients in a regression model.

Likelihood Ratio Test

A statistical test that compares the goodness-of-fit of two models—one may include a variable of interest, while the other does not, assessing whether the removed variable significantly affects model fit.

Interaction (Effect Measure Modification)

A situation where the effect of an exposure on an outcome differs depending on the presence or level of another variable.

Logistic Function

A function that models the probability of an event occurring, bounded between 0 and 1, often used in logistic regression.

Stratification

A method used in analysis that involves dividing a data set into subgroups or strata to control for confounding variables.

Case-Control Study Design

A type of observational study that compares individuals with a condition (cases) to those without (controls) to identify factors that may contribute to the condition.

Dummy Variable Coding

A method of converting categorical variables into a numerical format suitable for regression analysis by creating binary (0/1) columns for each category.

Covariates

Additional variables that are included in a statistical model to account for their influence on the outcome.

Natural Log of Odds Ratio

The logarithm of the odds of an event, used in logistic regression to estimate the relationship between predictor variables and a binary outcome.

Parameter Estimates

Values derived from statistical analysis that represent the relationship between predictors and outcomes.

Collinearity

A situation in regression models where two or more predictor variables are highly correlated, potentially leading to instability in the estimation of coefficients.

Statistical Significance

A measure of whether an observed effect in a study is likely due to chance or reflects a true association.

Iterative Solutions

Computational methods that refine estimates progressively through an iterative process until satisfactory accuracy is achieved.