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58 Cards in this Set

  • Front
  • Back
a computed disease rate that takes into acount the characteristics of the population so that rates in diff locales can be compred despite characteristics like age and gender
adjusted rate
the incidence of disease occurring during a limited period of risk (e.g the time span of a food borne outbreak of gastroenteritis)
attack rate
the proportion (percent) of people with disease who die w/in a specified time after disease onset
a disease rate that include all persons in a population w/o distinction with regard to age, gender, race, etc
crude rate
a databasse of information regarding all cases of certain disease that occur in a aspecficied population during a specified time period
disease register
infant mortality rate =
# of deaths children under 12 months / number of live births X 1,000 (per 1,000)
the number of deaths related to pregnancy of pregnant women in a year divided by the number of live births in that year (per 100,000)
maternal mortality rate
mortality =
the incidence rate of death
neonatal mortality rate
number of deaths of children under 28 days in a given year divided by the total number of live births in that year, times 1000
a disease for which notification of local health authorities is required
notifiable disease
the incidence of disease among contacts or household members following the occurrence of a primary case - the period observation is specified and usually brief
secondary attack rate
in survival analysis, when survival time for an individual is not observed because the individual was still alie at the end of the study or the subject is lost in follow up
censored data
a test for evalluating assocation between two variables in a contingency tabe. in the 2x2 tabel this test is equivalent to comparing proportions in two groups of patients
chi-squared test

chi-squared statistic would help you reject or accept the null
a rectangular array of numbers, typically croos classification of subjects into categries of two measurements
contignency table

comparing expected to observed then you would want to do a chi-squared test to see if this difference is due to chance or not
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 SBP in males versus females
independent samples T-test
Kaplan-Meier method (or Product-limit method
a procedure for estimating a survival function form survival data in presence of censoring
a tabulation showing the survival experience of a group of subjects over time. specifically showing the survival function estimated from data

1. divide follow up times into intervals
2. probability of dying during given interval is hazard (h = those who died / n entering interval)
3. prob of surviving that interval is 1-h
4. prob of surviving interval 2 is (1-h1)x (1-h2) ....
a statistical test for comparing two survival curves
log-rank test
the time at which 50% of the individuals have experienced the event of interest. the timepoint at which the survival fucntion crosses 50%
median survival
a statistical test for comparing the means of paired continuous measurements. this test is usually applied to the case where a single indivdidual is observed on 2 occasions (before and after)
paired-samples T-test

1. compute difference score for each observed pair (y1-y2 = d)
2. calculate mean of that (d)and the SD of difference scores
3. do a test statistic test
t=(mean d / SE)
statistical evaluation of time to event data. examples include time to death, time to disease progression, and time until onset to the disease
survival analysis
describes the probability that an individual will survive beyond a specific point in time
survival function
R squared
coefficient of determination
= 1 - (variation in Y not explained by X / total
variation in Y about mean)

describes proportion of total variation of dependent variable explained by its linear relationship w/ independent variable
e.g if it is .518 then the independent variable explains 51% of the variation in dependent
linear regression analysis, this is the proportion of total variation in the dependent variable explained by the independent variable
coefficient of determination (R squared)
how is the dependent variable different in a linear regression versus a logistic regression
in the linear regression the dependent variable is continuous. in the logistic regression it is dichotomous.
what is the dependent variable in a proportional hazards regression
survival time
explanatory variable is also called
the independent variable
an independent variable that takes on the values of 0 or 1 e.g to describe Male or F
indicator variable
a procedure based on minimizing the squared error, for estimating the intercept and slopes in a linear regression
least squares
a statistical analysis that predicts a continuous dependent variable using one or more independent variables
linear regression
a regression analysis procedure used to predict the value of a dichotomous variable. the effects of independent variables are usually presented as odds ratios
logistic regression

if the regression is higher than one than the variable is positively associated with the risk.
a linear regression analysis using two more more independent variables
multiple linear regression

y = a + (b1x1) + (b2x2) ....
a regression analysis using (linear, logistic, or proportional hazards) using two or more independent variables
multivariate regression analysis
a relationshiop in which the scatterplot of a dependent variable and an independent variable is not well approximated by a straight line
a regression analysis procedure used in survival analysis with censored data. the effects of the independent variables are usually presented as risk ratios
proportional hazards regression
an estimate of the intercept or slope in a regression analysis
regression coefficeint
a linear regression analysis using one independent variable
simple linear regression
the amount of change in the dependent variable when the independent variable increases by 1 unit
a regression analysis (any of the three) using one independent variable
univariate regression analysis
the difference between the riskds of the exposed group and the unexposed group
attributable risk
an analysis in which statistical account is made for potential confounding factors, so that an estimate of the independent effect of a risk factor can be made
adjusted analysis

could be via statistical modeling (regression techniques) or stratified analysis (breaking up confounding variables into narrow stratum or by doing separate analysis)
events that prevent the observation of a possible endpoint
competing risks
an indirect association of an exposreu with disease.
choosing exposed and unexposed subjects to have the same or similar values of some trait or exposreu - to control for confounding
matched analysis
a groupoing of subjects, typically formed for the purpose of adjustment (e.g age groups)
the error that resuts when one rejects the null when it is true or when one concludes there is a difference when there is not
type 1 error
the error that results when one does not reject the null and it is false or when one does not detect a diff when there is one
type II error
confining the analysis to one group of subjects to minimize confounding
restricted analysis
the probability that an evne will occur in a defined period of time
the probability of event in the exposed group / the probability of an event in the unexposed group
risk ratio
test statistic =
the effect / SE
the difference between the sample mean and the hypothesized mean
restricted activity day, work loss day and bed disability day are estimates of
the standard erroe =
SD over square root of n
the probability of a type I error is also called
statistical significance level
Prob that you reject null when it is true
confidence interval =
mean plus or minus 2 x SE
which risk (relative or atributable) indicateds best the causal relationship
relative risk
which risk (relative or attributable) is usually linked to indicating a clincal significance