Epidemiology and statistics Flashcards
(21 cards)
Sensitivity
The ability of a test to correctly identify those with a condition.
SENSITIVITY = TP /TP + FN
Specificity
The ability of a test to correctly identify those that do not have a condition.
SPECIFICITY = TN/TN + FP
Standard error of mean ( SEM)
SEM = SD/ square root (n)
Confounding
A variable that correlates with other variables within a study, leading to spurious results.
Correlation
Correlation is used to test for association between variables.
Linear regression
Linear regression may be used to predict how much one variable changes when a second variable is changed.
Type 1 error
the null hypothesis is rejected when it is true
Type 2 error
the null hypothesis is accepted when it is false
P value
p value is the probability of obtaining a result by chance at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. It is therefore equal to the chance of making a type I error
The power of a study
The power of a study is the probability of (correctly) rejecting the null hypothesis when it is false, i.e. the probability of detecting a statistically significant difference
Power = 1 - the probability of a type II error.
Power can be increased by increasing the sample size
The paired t test
The paired t test is appropriate for testing differences of means in a single group.
Log-rank test
Log-rank test can be used to test the difference in relapse rate between the two groups
Study Designs
Study design:
Levels of evidence
Ia - evidence from meta-analysis of randomised controlled trials
Ib - evidence from at least one randomised controlled trial
IIa - evidence from at least one well-designed controlled trial which is not randomised
IIb - evidence from at least one well-designed experimental trial
III - evidence from case, correlation and comparative studies
IV - evidence from a panel of experts
Grading of recommendation
Grade A - based on evidence from at least one randomised controlled trial (i.e. Ia or Ib)
Grade B - based on evidence from non-randomised controlled trials (i.e. IIa, IIb or III)
Grade C - based on evidence from a panel of experts (i.e. IV)
Meta- analysis
- Considered the ‘gold standard’ in terms of evidence
, meta-analysis is a statistical technique used to combine data from multiple studies to derive a more precise estimate of a treatment effect or association.
The primary goal is to increase power and improve estimates of the size of the effect, especially when individual studies may be too small (i.e. low-powered) to produce reliable results on their own
-Meta-analyses can be affected by publication bias, where studies with positive results are more likely to be published than those with negative or inconclusive results - Outcome points may include calculating pooled odds ratios, risk ratios, or mean differences
Likelihood ratio for a negative test result
Likelihood ratio for a negative test result - how much the odds of the disease decrease when a test is negative.
Sensitivity
Proportion of patients with the condition who have a positive test result
Specificity
Proportion of patients without the condition who have a negative test result.
Positive predictive value
The chance that the patient has the condition if the diagnostic test is positive.
Case Control study
The usual outcome measure is Odds Ratio.
Cohort study
The usual outcome measure is relative risk.
P Value
P value - is the probability of obtaining a result by chance at least as extreme as the one that was actually observed, assuming that the null hypothesis is true
