Statistics and Pharmacology Flashcards
Different data type. Give example of each:
- Categorical
- Nominal
- Ordinal
- Integer
- Discrete
- Continuous
- Ranked
- Categorical: Gender, Race, late preterm, early term etc.
Nominal = Categorical - Ordinal: ROP stages, APGAR scoring,
- Integer: count. number of accidents, number of hospital re-admissions
Discrete = Integer = Count - Continuous: weight, gestational age.
- Ranked: assigned a number rank. ranked list of leading causes of death. or leading causes of pediatric hospital admission.
Mean, Median and Mode
In right skewed distribution, where is the peak of the curve? where is each of the above from L to R
Mean
Median: values at which 50% of values are greater and 50% are
smaller.
Mode: most common value
Peak of the curve to Left
Mode (peak of the bell curve)
Median
Mean
Normal bell curve
Give percentage of the following:
within 1 SD
within 2 SD
within 3 SD
68 % (68.2%)
95 % (95.4%)
99.8%
Box Plot
Outlier:
Far Outlier:
Median
Qu
QL
Inner Fence
Outer Fence
outlier: between inner and outer fence
far outlier: outside outer fence
median: 50% ile
Qu: 75% ile
QL: 25% ile
Inner Fence: QL + 1.5x IQR = 95%
Outer Fence: QL + 3x IQR = 99%
What is Null Hypothesis (Ho)?
There’s no difference between the two groups.
What is Type 1 Error?
What is Type 1 Error also called?
Reject null hypothesis when it is true
False positive
Alpha Error
What is Type 2 error?
What is Type 2 error also called?
Accept the null hypothesis when it is false
False negative
Beta error
what is power ?
how to calculate power?
Probability of rejecting the null hypothesis when null hypothesis is false
(probability of detecting a difference if it exists)
1- Beta error
Calculate sensitivity/specificity/PPV/NPV and draw the 2x 2
Populations of 1000 babies. 100 babies have a disease
180 babies tested positive, among them 100 do not have the disease
What is the sensitivity, specificity, PPV, NPV.
Top: Disease : +, -
Left: Test: +, -
Sensitivity:
80 / 100
(portion of ppl who has the disease and tests positive)
–> needed for screening test.
Specificity:
800 / 900
(portion of ppl who does NOT have the disease and test negative)
PPV:
80 / 180
probability of having the disease when test is positive.
NPV:
800 / 820
probability of not having the disease when test is negative.
what are parametric tests for continuous data? (how to compare continuous data?)
2 groups:
- unpaired t-test
- paired t-test (compare two groups before and after)
3 or more groups:
- analysis of variance (ANOVA)
- multiple regression
What are parametric Tests for categorical data?
(how to compare categorical data?)
2 groups:
- chi-square
- McNemar’s (two paired groups)
3 or more groups:
- chi-square
- logistic regression
how is p-value related to type I error
p-value IS type I (alpha) error.
false positive rate
The probability of observing a difference by chance alone
Confidence interval:
Give some examples of how to explain confidence interval.
Based on the sample’s standard deviation and its size (i.e. given its standard error), we are 95% confident that the limits cover the true value for the population mean
OR, if we draw samples of the same size 100 times, 95 of those will include the true population mean
OR, ‘the results are accurate to within +/-2SD 950 times out of 1000’
(if cannot figure out, it’s fine)
case reports, case series and cross-sectional study
you just look at cases, exposure and outcome
case-control study
cases + controls (chosen by analyst)
you know the outcome,
you look at exposures
cohort study
cases + controls (chosen by analyst)
some has exposures and some no exposures.
You look at the outcome.
Relative Risk Reduction
what is it? how to calculate it?
what about Relative Risk?
“Risk of adverse outcome in the experimental group is reduced by this proportion relative to controls”
2 x 2
Top: Disease (+, -)
Left: exposure/intervention (+, -)
A, B
C, D
Control event rate: C/ (C+D)
Experimental event rate: A / (A+B)
Relative Risk or releative risk ratio. = experimental event rate / control event rate.
RRR= 1- Relative Risk
(measures of effect)
Odds Ratio
what is it? how to calculate it?
“Odds of adverse outcome in the experimental group is reduced by this proportion relative to controls”
Intervention Odds = A/B
Control Odds = C/D
Odds Ratio = Intervention Odds / Control Odds = (A/B) / (C/D)
OR will always overestimate the effect size compared to RR.
(measures of effect)
Absolute Risk Reduction
what is it? how to calculate it?
“Risk of adverse outcome in the experimental group is reduced by this absolute percentage.”
Absolute Risk Reduction = control event rate - experimental event rate
(ARR = CER - EER)
[ a / (a+b)] - [ c/ (c+d)]
ARR is aka attributable risk (AR) or risk difference (RD).
(measures of effect)
Numbers Needed to Treat
what is it? how to calculate it?
“Need to treat this many patients to avoid one adverse outcome”
NNT = 1/ Absolute Risk Reduction
(measures of effect)
Run Chart
what’s x-axis and what’s y-axis
what are 4 rules
what is the “run”
Y-axis: measure of interest
X-axis: unit of time
median line.
“run” = one or more consecutive data points on one side of the median
4 rules:
1. trend (5 or more)
2. shift (6 or more)
3. too many or too few runs (median data line crosses only once)
4. an astronomical data point.
Control chart elements:
x and y axis
x-axis: period
y-axis: precent
central line, upper control limit, lower control limit
SMART Aim
what does each letter represent
Specific
Measurable
Achievable
Relevant
Time Limited
Three component in QI
process
outcome
balancing measures
4 moral principles:
(Belmont Report)
Respect for persons > consent
Beneficence > risk & benefit
Justice > population
nonmaleficience > do no harm