Epidemiology and Biostates Pt. 4

Question 1

Regression analysis

Answer 1

used to estimate how the value of one variable corresponds to a value of another variable. A simple linear regression model uses X as the fixed non-random independent variable and Y dependent variables which are normally distributed. ie. predicting milk yield (Y) by parity in dairy cows (X).

Question 2

Multiple linear regression model

Answer 2

models the linear relationship between multiple independent variables (X’s) and a dependent variable (Y)

Question 3

Logistic Regression Model

Answer 3

used to model the relationship between an independent (quantitative or qualitative) variable and a dependent outcome variable that is discreet, often dichotomous. The outcome is expressed as an odds ratio

Question 4

Fisher’s Exact Test

Answer 4

used as a test of homogeneity, but when sample sizes are small since Chi-square tests are not accurate under small sample sizes

Question 5

Chi-Square Test of Association

Answer 5

done to determine whether or not there is an association between 2 or more proportions in differing populations (ie. test if there is a difference in color blindness between males and females)

Question 6

Chi-Square Test of Homogeneity

Answer 6

method for testing the null hypothesis that 2 or more population proportions are equal

Question 7

when are survival analysis studies done?

Answer 7

to monitor the progress or survival of patients undergoing a surgery or tx regimen. Can be used to compare median survival times for patients receiving competing medications

Question 8

Kaplan-Meier Procedure

Answer 8

determines the probability of surviving for a specific length of time considering censored data from the patients in the study

Question 9

Sign Test

Answer 9

considers the positive and negative outcomes of a trial or study and converts these +/- counts to a Binomial distribution. The probability of the number of positive or neg outcomes is then compared to the null hypothesis that the median of the differences should be zero

Question 10

Wilcoxon Signed Rank Test

Answer 10

can be used in the same setting as the sign test but it also incorporates the differences from the median in each data point, making it more informative and giving it more power than the sign test

Question 11

Type I error

Answer 11

rejecting the null hypothesis when it is true

probability of Type I error = a = level of significance

Question 12

Type II error

Answer 12

accepting the null hypothesis when it is false

probability of Type II error = B (beta)

Question 13

Power

Answer 13

probability of rejecting the null hypothesis when it is false (1-beta)

-a measure of the ability of a study to detect a true difference
-should be calculated prior to carrying out a study to determine the number of observations needed to detect a desired degree of difference

Question 14

T/F: if a study has an inadequate sample size, then the result with a null finding is uninformative

Answer 14

T

Question 15

case fatality risk (aka case fatality rate)

Answer 15

the proportion of persons with a particular condition (case) who die from that condition.
-A measure of the severity of the condition
-numerator is restricted to deaths among people included in the denominator

= # cause-specific deaths among the incident cases/number of incident cases

Question 16

point source epidemic curve

Answer 16

epi curve with a sharp upward slope and gradual downward slope. Usually the exposure period is relatively brief and all cases occur within one incubation period

Question 17

propagated epidemic curve

Answer 17

usually has a series of progressively taller peaks, each an incubation period apart. Happens in outbreaks that are spread from person to person and that may last longer than common source epidemics

Question 18

types of random sampling

Answer 18

1) stratified - layering a study population by each variable (ie. sex, age) we consider important and then randomize participants to tx groups within each stratum
2) simple - a subset of a population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group

Question 19

Pros/cons of stratified sampling

Answer 19

Pros:
-provides greater precision than a random sample of the same size and often requires a smaller sample size
-prevents an unrepresentative sample
-ensure we obtain sufficient sample points to support a separate analysis of any subgroup

Cons:
-more admin effort
-analysis is computationally more complex

Question 20

Pros/cons of simple sampling

Answer 20

Pros:
-more likely to represent the whole population
-quicker, cheaper, easier
-involves less judgment
Cons:
-risk of selecting samples from a few variations only
-redundant and monotony

Question 21

Steps of risk analysis

Answer 21

1) risk assessment (including determining whether a certain chemical is casually linked to particular health effects, performing a dose-response assessment, determining the extent of human exposure before or after the application of regulatory controls, and describing the nature and magnitude of the risk)
2) risk characterization (the estimated incidence of the adverse effect in a given population)
3) risk management (involves the evaluation of alternative regulatory actions and the selection of strategy to be applied)
4) risk communication

Question 22

What is bias?

Answer 22

an error in methodology that results in a systematic deviation of the result away from the truth

Question 23

random error is aka variability, random variation, or “noise in the system”

Answer 23

-can be minimized with large sample sizes
-has no preferred direction, will average out to having no net effect

Question 24

Internal vs. external validity

Answer 24

internal: ability of a study to measure what it intends to measure
-must be present to extrapolate to a different population

external: ability of a study to be extrapolated to a target population
-impacted by selection bias

Question 25

types of bias

Answer 25

confounding
information bias
selection bias
admission bias
prevalence/incidence
volunteer (self-selection)
losses to follow-up
inappropriate comparison group

Question 26

confounding

Answer 26

a mixing of effects that suggests an association where none exists or masks a true association
-occurs when a variable is associated with the exposure of interest and the outcome of interest, but is not the causal pathway

Question 27

information bias

Answer 27

results from problems with the info collected in the study, such as faults in the questionnaire

Question 28

selection bias

Answer 28

a problem with who is in the study, such as inappropriate detection of participants, self selection, non-response bias

Question 29

methods to control confounding

Answer 29

1) restriction/exclusion (selecting study participants with only one level of the confounding variable to eliminate effects of that variable)
2) matching (equalizes the frequency of the compounding variable in the groups being compared; select controls that are identical to cases in certain important characteristics)
3) analysis (collect data on potential confounding variables while conducting study-study data and then stratify the data based on these confounding variables)

Question 30

Reliability

Answer 30

a measure of the repeatability or reproducibility of a clinical measurement. Aka precision