BIOSTATISTICS Flashcards
specificity
TN / (TN + FP)
1-FP rate
what is beta value in biostatics
type II error
b = %
don’t confuse with power = 1 - b
what is 1 - beta in biostatics
power
100 - b = %
chai square test assess for statistically significant ____ between two or more ____ values
differences
categorical
i.e. percentages, alleles
(not means) = t-test
cross sectional study
aims to identify
prevelance
‘snap shot in time’ - **does not **follow patients over time
in cross over study, subjects recieve multiple treatments in ___
sequence
two or more treatments given to different patients groups
evaluates multiple independant variables simultaneously + interactions between variables
factorial study design
i.e. pts given vitamins: A only, C only, C+E, placebo
2 groups: 1 disease, 1 disease free. variables then compared.
study design?
case control
(OR)
disease –> risk factor
(retrospective)
2 groups: 1 risk factor, 1 risk factor free. disease then compared.
study design?
cohort
(RR)
risk factor —> disease
(anterograde)
* can be retrospective
ranges of correlation coefficient range between
and its strength
1 to +1
close to its margins = stronger
in correlation coefficient how are
r>0
r<0
interpreted
r>0 = positive = both values increase/decrease together
r<0 = negative = one value increases, other decreases
direction (positive, negative)
strength (-1 to +1) = stronger at poles
what study design can be useful in identifying risk factors potentially contributing to a disparity in the community being observed to help generate a research hypothesis
i.e. cross sectional study
(identify risk factors correlated to obesity in different settings - helps generate hypothesis)
OR of 1 means
OR >1 means
equally likely
exposure related to outcome
most time efficient experimental design to run
case control
You would need a case (people drinking high arsenic) and control (people with no arsenic).
intention to treat requires
all patients to be analysed in the group they were initally randomized
ignores deviations, withdrawals, compliance
used to preserve randomisation with attrition/crossover is introduced to study
which point locates ‘maximum sensitivity’
(A) = 100% sensitivity
all people who have disease test positive
moving cut point higher for a test =
decreases sensitivity
increases specificity
(increases FN, decreases FP)
equation for NNT
NTT = 1/ARR
(ARR = CER-EER)
CER = control event rate
EER = experimental control rate
don’t forget to do the 1/ at the end (not just calculate ARR)
Assume trace elements is control group, how many nulliparous women with confirmed pregnancies would have to be treated with folic acid to prevent one congenital abnormality?
NNT = 1/ARR
(ARR = CER-EER)
ARR = 2.3 - 1.3 = 1%
1/0.01 = 100 women
A study is conducted to assess body mass index (BMI) in a group of 100 patients with type 2 diabetes
mellitus. Results show a mean (± standard error of the mean) BMI of 31 kg/m 2 2
(± 4 kg/m ). The 99%
confidence intervals for this measurement are 20.7 to 41.3. The 95% confidence intervals are 23.3 to 38.8.
Based on this information, which of the following best represents the number of individuals who have a BMI
2 2
between 38.8 kg/m and 41.3 kg/m ?
A. 2
B. 4
C. 6
D. 8
E. 10
2
gaussian distribution question
roughly 2.5% between 95-99.7% confidence intervals
(here uses 99%). So 2% x 100 patients = 2 people
role of IKB in nuclear factor kappa B signal transuction pathway
NFKB bound to inhibitor protein IKB in cytoplasm (inactive)
when ligand binds (i.e. IL-1) –> activates IKB kiase (IKK complex) –> activated IKK phosphorylates IKB –> releases NFKB –> NFKB translocates to nucleus –> upregulates transcription/translation proinflammatory genes
increased** IL-6 **synthesis induced by this pathway
IKB = inhibitor of kappa B
IKK = IKB kinase complex
1-B (power) is the probabilty of ___ the null hypothesis when it is ___
rejecting
truly false
probability of finding a true relationship
= the probability of a statistical test correctly rejecting a false null hypothesis
detects a real effect when one exists
1-type II error
depends on sample size and outcomes being tested
typically set at 80% i.e. if B set at 0.2 = 1-B = 80%
B is probablity of commiting a
type II error
fail to reject null hypthesis when it is truly false
will miss true relationships
type I error
reject hypothesis when it is true
type II error
**fail to reject **hypothesis when it is false