Statistics/Evidence Flashcards
Levels of evidence for intervention studies?
1. 1++
2. 1+
3. 1-
4. 2++
5. 2+
6. 2-
7. 3
8. 4
- 1++
- High quality meta analyses, systematic reviews of RCT’s or RCT’s with very low risk of bias - 1+
- Well conducted meta- analyses, systematic reviews of RCTs, or RCTs with a low risk of bias - 1-
- Meta analyses, systematic reviews of RCTs, or RCTs with a high risk of bias - 2++
- High quality systematic reviews of case control or cohort studies; high quality case-control or cohort studies with a very low risk of confounding bias or chance and a high probability that the relationship is casual - 2+
- Well conducted case control or cohort studies with a low risk of confounding, bias or chance - 2-
- Case control or cohort studies with a high risk of confounding bias - 3
Non analytical studies (eg. Case reports, case series) - 4
Expert opinion, formal consensus
Z Values
1. Define
Important component of confidence intervals.
Measures the number of standard errors to be added and subtracted in order to achieve your desired confidence level.
80%z = 1.28
85%z = 1.44
90%z = 1.64
95%z = 1.96
98%z = 2.33
99%z = 2.58
Parametric data vs non parametric data
Parametric test eg. weight/age
- normal distribution of data
- data continuous
- independence of data (one group does not influence another)
- homogeneity
- considered more powerful tests
Non-Parametric Test:
- no assumptions with regards to distribution
- data can be continuous or ordinal
- can be transformed to parametric data
Examples of parametric tests?
- Paired t test
- Unpaired t test
- Pearsons
- Multiple regression
Examples of non parametric tests?
- Mann-Whitney U test
- Wilcoxon matched pairs test
Standard Deviation
Represents spread of the population
Odds Ratio
Represents the odds that a diseased group were exposed, compared to the odds of an undiseased group (controls) being exposed.
Eg. Smoking and lung cancer
Odds ratio
OR = 1
OR > 1
OR < 1
OR = 1 - no difference in the odds of exposure between the two groups
OR > 1 - diseased group more likely to have been exposed compared to controls
OR < 1 - diseased group less likely to have been exposed compared to controls
Calculating odds ratio
2x2 table
A = exposed patients, outcome +ve
B = exposed patients, outcome -ve
C = unexposed patient, outcome +ve
D = unexposed patient, outcome -be
OR = (A/C) / (B/D) = AD/BC
Confidence interval - define.
Small/narrow CI
Large/broad CI
Indicator of your measurements precision.
Small/narrow CI - if same question asked again for different sample population then we are reasonably sure the results would be similar.
- 95% CI + 95% sure of similar result
Large/broad CI - less sure of result, ?increase sample size to increase confidence
CI is influenced by sample size
Relative Risk
1. Define
2. Used in?
3. How to calculate ?
- Risk of a certain event happening in one group vs another
- Used in cohort studies
Use 2x2 table to calculate again.
RR = a/(a+b) / c/(c+d)
Sensitivity - define
Specificity - define
Sensitivity - the ability of a test to detect disease
Specificity - the ability of a test to detect health
Calculation for sensitivity
Sensitivity = (TP/TP+FN) x 100
True positive
False negative
Tests with low sensitivity - waste of time / money
Calculation for specificity
Specificity = (TN / TN + FP) x 100
True negative
False positive
Positive predictive value
1. Define
2. Formula
The chance that if the test is positive, the patient has the disease.
PPV = (TP/TP+FP) x 100
When prevalence increases, so does the PPV.
