# Error, Misclassification, and Bias Flashcards

What are the two types of error in epi inference?

Systematic bias and random error.

What is systematic bias?

Distortion of results of a study in a CONSISTENT manner.

What is random error?

Variability in data from one observation to the next. Dealt with via statistical methods.

Variance estimated in CI around estimate and presents random error.

How can we define validity?

Relative absence of bias or systematic error. Estimates are more valid as validity goes up and bias does down.

What is precision?

Define as relative lack of random error. More precise as sample size goes up.

What are some combinations of precision and validity?

Good precision (close estimates) with good validity (closely around bullseye-which is the truth)

Good precision and poor validity (close estimates but not close to target)

Poor precision and good validity (far away from each other but close to target)

What are the types of systematic bias?

3 types:

Confounding

Information Bias

Selection Bias

What is information bias?

Misclassification or measurement error.

Recall bias, for example.

What is selection bias?

Who is recruited. How they are recruited.

Who is retained and how.

What is bias towards the null versus away from the null?

Bias towards the null: estimate for RR and OR is closer to 1 compared to the true value. Observed is smaller than true magnitude.

Bias away from null: estimate from RR and OR is away from 1. Estimate is LARGER than true value.

What is sensitivity analysis?

Quantitative assessment to examine source of bias and amount of resulting uncertainty in studies.

How do we assess systematic bias versus how do we assess random error?

Random error usually assessed through statistical analysis.

Systematic error assessed through sensitivity analysis.

What is the general approach to sensitivity analysis?

4 steps:

- Hypothetical values used to create alternate estimates.
- Hypothetical values are given across a range to determine the range of possible inaccuracy around estimate.
- Range accounts for possible bias. What kind of estimate the readers should expect given a range around estimate we present as valid.
- CI estimates random error.

How we account for confounding in design?

RCT, stratification, restriction.

How do we account for confounding in analysis?

Standardization, stratification, and multivariate methods.