Statistics

Question 1

Clinical Significance

Answer 1

Practical importance of a treatment effect - whether it is real, genuine, palpable, noticeable.

Question 2

Clinical Trial

Answer 2

• any research study that prospectively assigns human participants or groups of humans to one or more health-related intervention to evaluate the effect on health outcomes.

Question 3

Confidence Intervals

Answer 3

Range of values so defined that there is a specified probability that the value of a parameter lies within it

Question 4

Data

Answer 4

Recorded, factual material

Question 5

Effect Size

Answer 5

• magnitude of an intervention, reflected by an index value
• independent of sample size
• calculated from data in a clinical trial
• most interventions have small to moderate effect size

Question 6

Effectiveness

Answer 6

Performance of an intervention under “real-world” circumstances

Question 7

Efficacy

Answer 7

Performance of an intervention under ideal and controlled circumstances

Question 8

False Negative

Answer 8

A test result which incorrectly indicates that particular condition or attribute is absent

Question 9

False positive

Answer 9

A test result which incorrectly indicates that a particular condition is present

Question 10

Fidelity

Answer 10

1. The extent to which delivery of an intervention adheres to the protocol or program originally developed
2. How close the intervention reflects the appropriateness of the care that should be provided

Question 11

Implementation Science

Answer 11

The science of putting (executing) a project or a research finding into effect

Question 12

Minimally Clinically Important Difference

Answer 12

• smallest difference in score in the domain of interest, which patients perceive as beneficial, mandating a change in patient’s management

Question 13

P-value

Answer 13

The probability, under an assumption of no difference in groups of obtaining a result equal to or more extreme than what was actually observed. Usually depicted at 5%

Question 14

Reliability

Answer 14

The degree to which the result of a measurement, calculation, or specification can be depended on to be precise.

Question 15

Statistical Assumptions

Answer 15

Characteristics about the data that need to be present before performing selected types of inferential statistics

Question 16

Statistical Significance

Answer 16

The claim that a result from data generated by testing or experimentation is not likely to occur randomly or by chance, but is instead likely to be attributable to a specific cause

Question 17

True negative

Answer 17

A test result that accurately indicates a condition is absent

Question 18

True positive

Answer 18

A test result that accurately indicates that a condition is present

Question 19

Validity

Answer 19

Extent that the instrument measures what it is designed to measure

Question 20

Nominal data

Answer 20

Two categories “yes or no” “boy or girl”

Question 21

Ordinal data

Answer 21

Has order, but no rank

- strongly agree, agree, disagree

Question 22

Interval

Answer 22

Has rank order: 1-4, 5-8, etc

Question 23

Ratio

Answer 23

Has rank, order, and countable.

Ex. Weight, temperature, age

Question 24

Parametric vs. nonparametric tests

Answer 24

1. Parametric tests = used when data is normally distributed
   — tests group means
2. Non-parametric = distribution-free test, don’t assume that your data follows a specific distribution.
   — used with smaller sample size
   — when you want to be more conservative with your analysis
   — tests group medians

Question 25

Tests of differences

Answer 25

• designed to measure differences in sample group means, medians, or proportions

Question 26

Tests of association

Answer 26

Used to discover if there is a relationship b/t two or more variables.

Question 27

Sensitivity Test

Answer 27

Proportion of pts who have the disease, who register a positive finding
- rule in

Question 28

Specificity

Answer 28

Proportion of pts who do not have the disease, who register a negative test finding
- rule out

Question 29

Positive predictive value

Answer 29

Probability that subjects with a (+) screening test, truly have the disease

Question 30

Negative predictive value

Answer 30

Probability that subjects with a (-) screening test, truly don’t have the disease

Question 31

Positive Likelihood Ratio

Answer 31

Reflects the probability of a pt with the disease + a positive test, divided by: probability of a pt without the disease+ a positive test.

• used to rule in a condition

Question 32

Negative Likelihood Ratio

Answer 32

Probability of a person who has the disease + negative test. Divided by: probability of a person who does not have the disease + negative test.

• commonly used to rule out a condition

Question 33

Accuracy

Answer 33

Calculated by examining the proportion of true positive and true negative in all evaluated cases

Accuracy = TP+TN/TP+TN+FP+FN

Question 34

Journal Impact Factor

Answer 34

Number of citations made in the current year to articles in the previous two years/total number of citable articles from the previous two years.