Biostats & Epi for PM Flashcards
(138 cards)
1
Q
Fetal Death Rate Equation
A
total number of fetal deaths in a given time period/total number of live births during the same period of time x 1000
2
Q
Infant Mortality Rate Equation
A
total number of deaths of infants (<1 y/o) in a time period/total number of live births during the same period x 1000
3
Q
Maternal Mortality Rate Equation
A
deaths due to pregnancy related illness in a given time period/total number of live births during the same period of time x 100,000
4
Q
Neonatal Mortality Rate Equation
A
total number of deaths of neonates (<28 days old) in a given time period/total number of live births during the same period of time x 1000
5
Q
Perinatal Mortality Rate Equation
A
neonatal deaths + fetal deaths in a given time period/total number live births and fetal deaths during the same time period x 1000
6
Q
ecological fallacy definition
A
an association at the population level is not necessarily true at the individual level
7
Q
studies with ecological fallacy
A
cross-sectional studies
8
Q
vital statistics recorded (4)
A
birth, death, marriage, divorce
9
Q
length bias definition
A
when a less aggressive disease appears to have a higher incidence because slower-moving diseases are more likely to be detected
10
Q
non differential bias is the same as
A
random error
11
Q
lead time bias definition
A
appearance that early diagnosis of a disease prolongs survival
12
Q
Hawthorne effect definition
A
individual behavior changes when a person knows they are being observed
13
Q
regression to the mean definition
A
the further a value is from the mean, the more likely future recordings are closer to the mean
14
Q
Neyman bias definition
A
selective survival bias
cases in a study have different exposures than the ones that die
15
Q
When does stratification reduce confounding?
A
analysis stage
16
Q
3 ways to reduce confounding during the design stage
A
randomization
restriction
matching
17
Q
3 ways to reduce confounding during the analysis stage
A
standardization
stratification
statistical modeling
18
Q
Bayes theorem equation
A
(prevalence)(sensitivity)/(prevalence)(sensitivity) + [(1-prev)(1-specificity)]
19
Q
incidence density definition
A
number of new cases of a disease per summation of time that each person is at risk of a disease in a specified time and place
20
Q
incidence density equation
A
new cases/sum of person-time
21
Q
central limit theorem definition
A
when there are a large amount of mutually independent random variables, the mean population will approach normal distribution (n >30)
22
Q
IQ mean and SD
A
100 +/- 15
23
Q
z-score definiton
A
how many standard deviations are between an observed value and the mean
24
Q
z-score equation
A
observed value - mean / standard deviation
25
rule of addition equation
event 1 + event 2 - (event 1 and event 2 overlap) = probability
used for non-mutually exclusive events
26
standard mortality ratio equation
observed # of deaths/expected # of deaths x 100
27
direct adjustment
when you use a second population to extrapolate estimates
28
null hypothesis definition
there is no difference between the variables being tested
29
type 1 error definition
when a null hypothesis is rejected when it is actually true (ex. false-positives)
30
type 2 error definition
when a false null hypothesis is not rejected (ex. false negatives)
31
confidence interval equation
mean +/- 1.96(std dev/sq root N)
32
as prevalence increases, PPV _____ and NPV ____
increases, decreases
33
power equation
1 - beta = 1- the probability of rejecting the null when the null is true
34
3 ways to increase power
increase sample size
decrease beta
increase threshold of Ho
35
NNT equation
1/ARR = 1/risk exposed - risk unexposed
36
NNH Equation
1/absolute risk increase
37
9 components to determine causality
1. consistency of association
2. strength of association
3. specificity
4. temporal factors
5. coherence of explanation
6. biological plausibility
7. experimental evidence from a controlled trial
8. dose-response relationship
9. analogy
38
Standard error equation
std dev/sq root n
39
internal validity definition
how well a study represents the true association within a study
40
external validity definition
how well the results of a study are generalizable to a different population
41
degrees of freedom equation
(rows-1)(columns-1)
42
chi squared equation
sum of (observed data-expected data)sq/expected data
expected= (rows)(columns)/total
43
Kappa equation
observed agreement/chance agreement/total number-chance agreement
observed: agreed true + agreed false
cell agreement due to chance = (row total)(column total)/(total number)
chance agreement = TT chance + FF chance
44
F test
part of ANOVA
45
confounder definition
3rd variable associated with the exposure and the outcome
| obscured the relationship between the exposure and outcome
46
effect modifier definition
changes the relationship between exposures and outcomes
47
intervening variable defintion
a mechanism by which a causal variable leads to an outcome
48
necessary cause definition
required for disease to occur but may not invariable lead to disease
49
sufficient cause definition
invariably leads to a disease
50
coefficient of determination definition
the proportion of variation of a dependent variable that can be explained by an independent variable
51
3 examples of time-series analysis
cohort studies
epidemic studies
longitudinal data
52
McNemar's Test definition
chi-sq test for non-independent variables, allows you to analyze matched pairs or calculate before and after in the same variable
53
Mann-Whitney U test definition
tests the median between two groups, the nonparametric version fo the t-test
54
attributable risk equation
a/a+b - c/c+d
55
relative risk equation
(a/a+b)/(c/c+d)
56
OR equation
(a/c)/(b/d)
57
25th percentile calculation
(n+1)/4
58
sign test defintiion
nonparametric test that compared dichotomous differences in data from matched otherwise identical pairs, ignored magnitude of difference
59
Nonparametric version of t-test
mann-whitney U test
| wilcoxon rank-sum test
60
Nonparametric version of paired t-test
Wilcoxon signed rank test
| sign test
61
Nonparametric version of ANOVA
Kruskal-wallis test
62
Nonparametric version of Pearson correlation
spearman correlation
| chi-sq
63
regular categorical variable example
group names, M/F
64
ordinal variable definition
group names with an order, ex. cancer stage
65
continuous variable definition
measurements, ex. height/weight
66
discrete numeric variable example
counts, ex. number of crashes at an intersection
67
interval variable definition
continuous variable with no true zero
68
ratio variable definition
continuous variable with a true 0
69
variance equation
average squared distance from the mean
70
standard deviation equation
square root of variance
71
right skew effect on measures of central tendency
mean > median
| tail goes to the right
72
left skew effect on measured of central tendency
mean < median
| tail goes to the left
73
geometric mean for skewed data equation
mean of logs = e^mean
74
coefficient of variation equation
ratio of std dev to the mean x 100
| SD/mean x 100
75
2 uses of coefficient of variation
1. compare relative data spread for 2 variables
| 2. evaluate precision of the measurement of a single variable
76
z score definition
number of standard deviations a value is away from the mean
77
percentile of z=0
50th percentile
78
percentile of z=1
84th percentile
79
percentile of z=2
97.5th percentile
80
z score equation
z = obs value - known sample mean / population std dev
81
4 types of random samples
simple random sample
stratified random sample
cluster random sample
systematic random sample
82
central limit theorem
distribution of sample means is approximately normal if the sample size is large enough (N~=30)
83
standard deviation of distribution of the sample mean equation
AKA standard error
| std dev/sq root N
84
95% CI equation
sample mean +/- 2(pop sd/sq root sample size)
85
two sided null and alternative hypotheses
H0: mu1 = mu0
HA: mu 1 does not = Mu0
86
one sided null and alternative hypotheses
```
H0: mu1 >= M0
HA mu1 < Mu0
OR
H0: Mu <= M0
HA Mu1>M0
```
87
3 steps to hypothesis testing
1. calculate test statistic
2. identify probability distribution of the test statistic
3. calculate p-value from test statistic based on probability distribution
88
How do you reduce type 1 error?
select a smaller alpha
89
decrease alpha, sample size ___ and Power ___
increases, decreases
90
to detect smaller differences between samples, sample size should be _____ and power should ____
increased, decrease
91
4 tests available for continuous outcome/categorical predictor with 2 groups`
t-test
Wilcoxon rand sum (NP)
mann-whitney U test
median test
92
2 tests available for continuous outcome/categorical predictor with >2 groups
ANOVA
| kruskal-wallis (NP)
93
3 test available for paired continuous outcome/categorical predictor
paired t-test
Wilcoxson signed rank (NP)
sign test
94
3 tests available for categorical outcome/categorical predictor
chi squared
fisher's exact test
paired--McNemar's chi squared
95
3 tests available for continuous outcome/continuous predictor
Pearson's
spearman's (NP)
linear regression
96
Test for categorical outcome/continuous predictor
logistic regression
97
When should you use nonparametric tests? (3)
to convert values to rank--then analyze rank
with small sample sizes
with ordinal outcomes
98
2 sample t-test use and output
use: compare continuous outcome between 2 groups when the data is symmetric or n>15
outcome: t-statistic --> p-value
99
Wilcoxon rank-sum test use and output
use: compare continuous outcome between 2 groups when the data is skewed, small n, or ordinal data
output: rank overall --> compare sums of ranks between 2 groups
100
Median test definition
overall median across entire sample
| asks whether each value is > or < median and compares via a 2x2 table and chi-squared
101
Paired t-test use
compare continuous outcomes in pairs
| looks at mean difference of pairs then asks is it different y/n by one-sample t test
102
Wilcoxon signed rank use
continuous outcomes in pairs when there are few pairs or data is skewed
103
Sign test use
continuous outcomes in pairs when you don't have numbers, only relationships
104
ANOVA use
comparing continuous outcomes between >2 groups
105
Kruskall Wallis Use
comparing continuous outcomes between >2 groups when you have skewed sample, small n, ordinal data
compares sums of ranks or groups
106
Fisher's exact test use
small sample size for categorical outcome/categorical predictor (any cell <5)
107
McNemar's chi-squared use
chi-sq for matched or paired proportions (ex. matched case-control)
108
r^2 definition
the amount of variability accounted for by the line of best fit
109
correlation coefficient equation
sq root of r^2
110
r=0.2 is ____ correlation
weak
111
r=0.4 is _____ correlation
moderate
112
r=0.8 is _____ correlation
strong
113
Linear regression use
continuous outcome w continuous predictor
114
F test equation
MSfitted/MSerror with p-1, n-1 DFs
115
Multicolinearity definition
When 2 or more predictor variables are highly correlated
116
Multicolinearity consequences (2)
increases standard error of beta estimates
| can lead to confusion/misleading results
117
ANCOVA use
used to compare means between groups while controlling for other variables (covariates) that may be unbalanced between groups
118
logistic regression use
categorical outcome/continuous predictor
| betas are estimated from maximum likelihood--model gives the probability of the outcome
119
Who determines which diseases are notifiable?
Council of Territorial and State Epidemiologists
120
Sensitivity definition
the proportion of those that have a diseases that are accurately defined as having it (SNOUT)
121
Specificity definition
those without a disease that are accurately identified as NOT having it (SPIN)
122
Multiplication rule equation
P(event 1 and event 2) = P(1) x P(2)
123
Multiplication rule use
determine the probability of 2 independent events
| can also use to test for independence
124
Addition rule equation (mutually exclusive)
P(1 or 2) = P(1) + P(2)
125
Addition rule equation (not mutually exclusive)
P(1 or 2) = P(1) + P(2) - P(1 and 2)
126
I^2 Statistic definition
total variation in a study estimate due to heterogeneity between studies (for meta-analysis)
If >50% --> heterogenous
127
Kaplan-Meier curve statistical test
log rank test
128
Cox proportional hazards test
hazard ratios
129
Common source outbreak pattern
a group of people become ill after being exposed to a point-source contaminant
130
Continuous common source outbreak pattern
a common source continuously affects this who come into contact with them
131
Propagated outbreak pattern
infection is transmitted from one person to another
132
Mixed outbreak pattern
when a common source outbreak is complicated by person-to-person spread
133
Meta-analysis output for categorical variables
OR
134
Meta-analysis output for continuous variables
mean differences
135
sensitivity + ______ = 1
false negative error rate
136
specificity + _____ = 1
false positive error rate
137
ILINet Case Definition (3)
fever >100
cough +/- sore throat
if flu swab + ok
138
How does NHANES get its data?
home interviews and PEs
