Boards, Kaplan, Biostat

Front 1

binary or dichotomous variable

Back 1

only two values. yes/no. male/female

Front 2

ordinal variable

Back 2

there's an inherent ranking. but they do not be scalar. ex. low, medium, or high prognosis. but unlike continuous variable, the different b/w low and medium rank do not have to be the same difference between medium and high rank.

Front 3

if there was a perfectly normal curve then what 3 things should be same?

Back 3

mean, median, mode

Front 4

disadvantages of mean

Back 4

1. doesn't tell distribution
2. affected by outliers

Front 5

advantage of median

Back 5

less affected by outliers than mean

Front 6

skewed distributions. positive skew means?

Back 6

that the longer tail is on the positive end. so the mean> median.

Front 7

nonparametric tests is used when the samples are?

Back 7

when sample size is small or samples are noncontinuous.
nonparametric tests makes no assumptions about the underlying distributions of the data being compared in the 2 groups.

Front 8

deviance = ?

Back 8

sum ((xi-X)^2)

Front 9

variance = ?

Back 9

deviance/(N-1)

Front 10

STD = ?

Back 10

sqr(variance).
X+/- 1.96 of STD = 95% confidence interval

Front 11

4 different ways to do bivariate comparisons?

Back 11

1. absolute difference (15%-10%)
2. relative difference (15%/10%)
3. percent difference ((15%-10%)/15%))
4. comparison of the means

Front 12

alpha

Back 12

probability that represents the experimenter's tolerance for rejecing the null hypothesis due to chance alone.
when alpha is 0.05, then when null hypothesis is rejected there is only 5% chance that the data difference actually happened by chance.

lower the alpha set, more rigorous the standard for testing the null hypothesis.

Front 13

p value

Back 13

the probability that the difference in data happened by chance.
less the p value, less likely that the difference happened by chance

reject null hypothesis when p<alpha
accept null hypothesis when p>alpha

Front 14

chi square is used to ?

Back 14

to compare the 2 distributions of scores. sum of (O-E)^2/(E)

to compare noncontinuous data in two groups.

Front 15

student's t test

Back 15

parametric test to compare 2 means derived from 2 samples

Front 16

paired t test

Back 16

used when an observation is made twice on a sample.
t = Difference / (squroot (std error of difference/number of subjects))

Front 17

examples of permutation tests

Back 17

Fisher's exact test
Pittman Welch permutation test
these consider all possible permutations of the data and compare them w/ the actual values

Front 18

ranking tests

Back 18

Ex. Wilcoxon test, Mann-Whitney U test

Front 19

Spearman rank order formula

Back 19

used for data that is continuous and based upon some ranking. this is for making correlation coefficient

Front 20

Pearson product-moment correlation formula

Back 20

used for ranked data that have no intrinsic numerical value.

Front 21

a positive correlation between "a" and "b" can be interpreted as ? (3 different ways)

Back 21

1. a causes b
2. b causes a
3. c causes both a and b

Front 22

beta tests for ?
alpha tests for?
(false ___)

Back 22

beta - false negative (type II error).
accepting null hypothesis when it is not true

alpha - false positive (type I error). rejecting the nulll hypothesis when there is no significant difference

Front 23

Power

Back 23

probability of rejecting the null hypothesis when it is false. higher the better.
power = 1 - beta. so you want smaller beta.

higher the power, the more ability the study had to detect a true difference between the two groups

when pB <0.05, there is less than 5% chance that the study was not powerful enough to detect a true difference.

Front 24

explained variance (R2)

Back 24

higher the explained variance, the more likely it is that the independent variable is responsible for all of the variation.

Front 25

in multilinear regression analysis, when the m is bigger

Back 25

it means that that variable has a bigger effect

Front 26

in logistic regression the y is

Back 26

a binary variable

Front 27

discriminant function analysis, the outcome of interest is __

Back 27

categorical
ex. bilirubin AST, ALT when testing liver functions

Front 28

3 different types of multivariable models

Back 28

1. logistic regression
2. ANOVA
3. discriminant function analysis

Front 29

sensitivity is?

Back 29

probability that the individuals w/ the disease would be correctly identified as having the disease.

Front 30

specificity is?

Back 30

probability that the individuals w/o the disease would be correctly identified as nondisease by the test.

Front 31

PPV is?

Back 31

probability that the individuals who test positive for the disease actually have the disease.

Front 32

NPV is?

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probability that the individuals who tested negative for the disease actually do not have the disease.

Front 33

advantages of randomized controlled trial?

Back 33

it is considered to be the most rigorous and powerful approach to answering clinical q's.

Front 34

cross-over randomized controlled trial: adv? when can it not be used?

Back 34

adv: this adds analytical power over the randomized trial. this can decrease the number of samples

not used: when disease change very rapidly or are unpredictable

Front 35

non-experimental designs are used when?

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when the disease is rare and it would be impossible to follow 1000s of samples for years. so you do a retrospective study
this will create more bias

Front 36

4 types of nonexperimental designs

Back 36

1. case-control
2. cohort
3. cross sectional
4. longitudinal

Front 37

case control study is?

Back 37

identify ppls on the basis of the same outcome/disease and previous experiences w/ various exposures.
case = ppls w/ cancer
control = w/o cancer
cases and controls are the same except that they have cancer or not.

Front 38

odd ratio

Back 38

used in case-control study. ad/bc.
if the odds ratio is 7.5 and then pt w/ cancer is 7.5 times more likely to have been a smoker.

Front 39

cohort study is?

Back 39

pts w/ common experience (like exposure) are assembled and monitored until an outcome appears.

use relative risk and attributable risk.
relative r = incidence (exposed) over incidence unexposed.
attributable risk = incidence exposed - incidence unexposed

Front 40

advantage of cohort study over case-control studies

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1. less bias, like recall bias
2. can control level of exposure/experience

cohort = definitive observational clinical study

Front 41

crude birth rate is?

Back 41

# newbirth/total population. can be misleading for an indicator of pop growth cuz it doesn't show # of baby death

Front 42

crude mortality rate is?
crude rate of natural increase

Back 42

# of deaths from all causes per year divided by the total population

crude birth rate - crude death rate

Front 43

infant mortality rate?
neonatal mortality rate
postnatal mortality rate

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# of deaths until 1st yr/ total number of live births
w/in first 4 wks
after 4 wks but before 1st bday

Front 44

life expectancy is?

Back 44

median survival time.
uses cross-sectional mortality rates for each age to summarize mortality across the life-cycle for a given population.

Front 45

detection bias

Back 45

more info is solicited from teh tx group asopposed to the placebo group. solved by double-blind studies

Front 46

proficiency bias
referral bias (sampling bias)

Back 46

the intervention under study is delivered w/ unusual skill or incompetence so can't be reproduced

sampling error

Front 47

susceptibility bias
recall bias
ascertainment bias

Back 47

when pts w/ severe conditions get a different intervention. do "randomizing" of patients
pts can't remember well, this is in retrospective studies

pts w/ suspected outcome are more extensively probed.

Front 48

lead time bias
measurement bias

Back 48

when screening test can detect a disease earlier than before, and ppls think that that test is allowing longer survival of the pts
the act/fact of measuring changes what is being measured (ex. BP) (ex. Hawthorne Effect = when pts who know they are being assessed act differently becasue they are being observed)