Biostatistics Flashcards
Steps or Path to publication
- BEGIN With a RESEARCH QUESTION
- DESIGN the STUDY
- ENROLL the SUBJECTS
- COLLECT the DATA
- ANALYZE the DATA
- PUBLISH
BEGIN With a RESEARCH QUESTION
Write a null hypothesis
DESIGN the STUDY
RCT
Case-Control
etc.
ENROLL the SUBJECTS
Assign treatment groups or identify subjects belonginging to a cohort or other group
COLLECT the DATA
Prospective
Retrospective
ANALYZE the DATA
Enter into statistical database
Continuous data has a logical order with values that continuously increase (or decrease) by the same amount. The two types of continuous data are?
interval data and ratio data
interval data has no meaningful zero
Celsius temperature scale is an example of interval data because it has no meaningful zero (0°C does not mean no temperature; it is the freezing point of water).
ratio data has a meaningful zero
(zero equals none)
Heart rate is an example of ratio data; a HR of 0 BPM is cardiac arrest (zero equals none; the heart is not beating).
RATIO DATA
Equal difference between values, with a true, meaningful zero
(0 = NONE)
Examples: age, height, weight, time, blood pressure
NTERVAL DATA
Equal difference between values, but with out a meaningful zero
(O does not = NONE)
Examples: Celsius and Fahrenheit temperature scales
DISCRETE (CATEGORICAL) DATA
Data fits into a limited number of categories
NOMINAL DATA
Categories are in an arbitrary order
Order of categories does not matter
Examples; gender, ethnicity
ORDINAL DATA
Categories are ranked in a logical order, but the difference between categories is not equal
Order o f categories matters
Examples: NYHA Functional Class l-IV;
0-10 pain scale
The mean is preferred for
continuous data that is normally distributed
The median is preferred for
ordinal data or continuous data that is skewed
The mode is preferred for
nominal data
Standard deviation (SP):
indicates how spread out the data is, and to what degree the data is dispersed away from the mean
Characteristics of a Gaussian Distribution
68% of the values fall within 1 SD of the mean and 95% of the values fall within 2 SDs of the mean.
An independent variable
is changed (manipulated) by the researcher
dependent variable
The dependent variables can be affected by the independent variables
Null hypothesis
What the researcher is trying to reject
The null hypothesis states that there is no significant difference between two treatment groups.
Example: Xarelto is equal to orange tic tacs in the prevention of blod clots.
When investigators design a study, they select a maximum permissible error margin, called?
alpha (a).
The p-value is compared to alpha. If alpha is set at 0.05 and the p-value is less than 0.05, the null hypothesis is?
rejected, and the result is statistically significant.
A confidence interval (Cl) provides the same information about significance as the p-value, plus the precision of the result.
CI = 1 - a
Type-I Errors
False positives
Results stated significance when in fact there was no significance and null hypothesis should have been accepted.
Type II errors
False Negative
The null hypothesis was accepted when it should have been rejected
Study power
The ability to avoid a Type II error (False Negative)
Power = 1-beta
beta is usually set to 0.1 or 0.2 (10% or 20%)
Risk
Total people in the group with an Unfavorabel Event [UE] (all the things that went bad) / Total number of people in the group [TIG] (How many people could have had a bad event)
UE / TIG
Odd ratio formula
Senstivity and apecificity formula
Senstivity and specificity formula (different look)
Recall for ratio data, the result is not statistically significant if the confidence interval ?
crosses one, so the vertical line
