Biostat post Q2

Question 1

censored data

Answer 1

In survival analysis, when the survival time for an individual is not observed because the individual was still alive at the end of the study or the subject is lost to follow-up.

Question 2

chi-squared statistic

Answer 2

sum (O-E)^2 /E

The test statistic from a chi-squared test.

–> if the chi-squared statistic for a comparison of two proportions exceeds 3.84, then the difference is statistically significant with p

Question 3

What is the primary limitation of the chi-squared test?

Answer 3

The chi-squared test gives a p-value but provides no estimate of the size of the effect.

Question 4

After using the chi-squared test, how do you estimate the size of an effect?

Answer 4

–> Difference of proportions (risk difference)

–> Ratio of proportions (relative risk)

–> Risk of odds (odds ratio)

Question 5

Contingency table

Answer 5

A rectangular array of numbers, typically cross-classifications of subjects into categories of two measurements

Question 6

Independent Samples t-test

Answer 6

A statistical test for comparing the means on a continuous measurement for two separate groups of individuals.

–>For example, this test can be used to compare mean systolic blood pressure in males versus females.

Question 7

Kaplan-Meier method

Answer 7

See Product-limit method


A procedure for estimating a survival function from survival data in the presence of censoring.

Question 8

survival analysis

Answer 8

Statistical evaluation of time-to-event data. Examples include time to death, time to disease progression, and time until onset of disease.

Question 9

survival curve

Answer 9

A graph of a survival function.

Question 10

survival function

Answer 10

Describes the probability that an individual will survive beyond a specific point in time.

Question 11

survival time

Answer 11

Data measured as the time until an event (such as death) occurs.

Question 12

coefficient of determination

Answer 12

Usually denoted by R^2, in linear regression analysis,

–>This is the proportion of total variation in the dependent variable explained by the independent variable(s).

Question 13

correlation coefficient

Answer 13

Usually denoted by r

–>this is a measure of the strength of a linear relationship between two variables.

–>The correlation coefficient is always between –1 and 1, where either extreme denotes a perfect linear relationship and a correlation of zero denotes no linear relationship.

–>Positive values of r denote a positive relationship, and negative values of r denote an inverse relationship

Question 14

Cox regression

Answer 14

See Proportional hazards regression.

A regression analysis procedure used in survival analysis with censored data. The effects of independent variables are usually presented as risk ratios.

Question 15

dependent variable

Answer 15

In a regression analysis, the dependent variable is the variable which is predicted by the model.

–>In linear regression, the dependent variable is continuous.

–>In logistic regression, it is dichotomous.

–>In proportional hazards regression, it is a survival time.

Question 16

dichotomous variable

Answer 16

A categorical variable having only two levels (e.g., presence or absence of disease)

Question 17

explanatory variable

Answer 17

Independent variable


A variable which is used to predict the dependent variable in a regression analysis.

Question 18

independent variable

Answer 18

A variable which is used to predict the dependent variable in a regression analysis.

Question 19

Indicator variable

Answer 19

An independent variable that takes on the values 0 or 1.

–>For, example, to indicate female gender, an indicator variable will be set to 0 for the males and 1 for the females.

Question 20

intercept

Answer 20

In a linear regression analysis, the mean of the dependent variable when the independent variables are all set equal to 0.

Question 21

least squares

Answer 21

A procedure, based on minimizing the squared error, for estimating the intercept and slopes in a linear regression analysis.

Question 22

linear regression

Answer 22

A statistical analysis that predicts a continuous dependent variable using one or more independent variables based on a the equation of a line.

Question 23

logistic regression

Answer 23

A regression analysis procedure used to predict the value of a dichotomous variable. The effects of independent variables are usually presented as odds ratios.

Question 24

multiple linear regression

Answer 24

A linear regression analysis using two or more independent variables.

Question 25

multivariate regression analysis

Answer 25

A regression analysis (linear, logistic or proportional hazards) using two or more independent variables.

Question 26

non-linear

Answer 26

A relationship in which the scatterplot of a dependent variable and an independent variable is not well-approximated by a straight line.

Question 27

proportional hazards regression

Answer 27

A regression analysis procedure used in survival analysis with censored data. The effects of independent variables are usually presented as risk ratios.

Question 28

regression coefficient

Answer 28

An estimate of the intercept or slope in a regression analysis.

Question 29

response variable

Answer 29

See Dependent variable.

–>In a regression analysis, the dependent variable is the variable which is predicted by the model.

–>In linear regression, the dependent variable is continuous.

->In logistic regression, it is dichotomous.

–>In proportional hazards regression, it is a survival time.

Question 30

scatterplot

Answer 30

A 2-dimensional plot of a dependent variable (usually on the vertical axis) and an independent variable (usually on the horizontal axis). Each point on the plot represents on subject from whom both variables are measured.

Question 31

simple linear regression

Answer 31

A linear regression analysis using one independent variable.

Question 32

slope

Answer 32

In a linear regression analysis, the amount of change in the dependent variable when the independent variable increases by 1 unit.

Question 33

univariate regression analysis

Answer 33

A regression analysis (linear, logistic or proportional hazards) using one independent variable.

Question 34

Bradford Hill criteria

Answer 34

Characteristics that may indicate causal associations in biology:

–>strong association

–>dose-response relationship

–>consistent association

–>specific association

–>temporally correct association

–>biologically plausible association.

Question 35

Early detection

Answer 35

Any action that advances the time of awareness that a disease is present.

Question 36

lead time

Answer 36

The increased time from diagnosis to death (or other outcome) due to earlier diagnosis as opposed to later death.

Question 37

length-biased sampling

Answer 37

In a screening program, the tendency to detect indolent disease with a relatively good prognosis.

Question 38

Occult disease

Answer 38

Disease is detectable by testing but not evident by signs or symptoms.

Question 39

pre-clinical detection period

Answer 39

The time interval when a disease can be found using screening techniques, but before symptoms would bring it to clinical attention.

Question 40

Primary prevention

Answer 40

An attempt to avoid any manifestations of disease. (Lowering cholesterol in people without heart disease.)

Question 41

pseudodisease

Answer 41

Subclinical disease that would not become overt before the patient dies of other causes, or which would never progress to clinical recognition.

Question 42

Screening

Answer 42

The systematic examination of those who are apparently well (or who are apparently free of the target disease) to identify and treat subclinical disease (or predictors of future disease).

Question 43

secondary prevention

Answer 43

An attempt to avoid progression of a disorder among individuals who already have some signs (or symptoms) of the target disease (e.g., lowering colesterol in heart attack patients).

Question 44

subclinical disease

Answer 44

See occult disease.

Disease is detectable by testing but not evident by signs or symptoms.


Question 45

target disease

Answer 45

A disease or condition that is targeted by a screening program.

Question 46

target population

Answer 46

A population selected for screening.