Common Statistical Test and r Flashcards
T - test example
Comparing the mean blood pressure between men and women
Common statistical tests
- t-test
- ANOVA
- Chi-square (x^2)
ANOVA test - action
Checks differences between means of 3 or more groups
ANOVA test example
Comparing the mean blood pressure between members of 3 ethnic groups
Chi-square (x^2) test
Checks differences between 2 or more PERCENTAGES OR PROPORTIONS od caregorcal outcomes
Chi-square (x^2) example
Comparing the percentage of members of 3 different ethnic groups who have essential hypertension
T test
Checks differences between MEANS OF 2 groups
Pearson correlation coefficient (r): range
-1 …..+1
the closer the absolute value of r is to 1
the stronger the linear correlation between the 2 values
positive r value –>
positive correlation: as one variable increases, the other variable increases
negative r value –>
negative correlation:as one variable increases, the other variable decreases
Coefficient of determination
r^2 (value that is usually reported)
Pearson correlation coefficient - symbol
r
epidemiology - r - means?
Pearson correlation coefficient
ANOVA meaning
Analysis of Variance
t-test vs ANOVA vs CHI-square according to action
t-test –> checks difference between means of 2 groups
ANOVA –> Checks differences between means of 3 or more groups
CHI-square –> Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values)
ROC
receiver operating characteristic
ROC (receiver operating characteristic) - definition and explanation
is a graphic representation between sensitivity (y axis) and 1-specificity (FP rate) (x axis) for a diagnostic test
explanation –> the closer the curve is to the diagonia, the less discriminating ability of the test. The closer the curve to the y axis, the better discriminating ability of the test
variables - definition
a quantity that changes under different circumstances
variables - types
- independent variables
2. dependent variables
independent variables?
characteristics that an experimenter can change (eg. amount of salt in a diet
dependent variables?
outcomes that reflext the experimental change (blood pressure under different salt regiments)
t test - types (explain)
independent (nonpaired) –>2 different groups of persons are sampled on one occasion (eg. one group with the drug A, and one group with the drug B)
dependent (paired) –> The same persons are sampled on 2 occasions (before and after the treatment)
ANOVA - types (explain)
- one way analysis –> 1 variable (eg. weight loss mean in 3 different programs)
- 2 way analysis –> 2 variables (eg. weight loss mean in 3 different programs and men vs women)
Meta-analysis?
a statistical procedure that integrates the results of several independent studies considered to be combinable
