Statistica

Question 1

Bot plot

Answer 1

Box always shows the median and the two quartiles (the 1st and the 3rd)

The whiskers of the box plot can represent different values depending on the specific box plot.

Question 2

Use of box plot

Answer 2

comparing data between many sets of data, such as many different populations.

Question 3

Pre-clinical.

Answer 3

Animal/cell testing to gather information about efficacy and toxicity.

Question 4

Phase 0

Answer 4

small group of volunteers, used to assess pharmacodynamics and pharmacokinetics

Question 5

Phase 1

Answer 5

Testing of drug on healthy volunteers to find appropriate dosing

Question 6

Phase 2

Answer 6

Testing of drug on large group of patients to assess efficacy and safety

Question 7

phase 3

Answer 7

Testing of drug on a large group of patients to confirm effectiveness, safety and comparing to existing interventions

Question 8

Confidence intervals

Answer 8

range within which the true treatment effect is likely to lie.

Question 9

Sensitivity

Answer 9

proportion of people with the condition who will have a positive result

Sensitivity = a/(a+c)

Question 10

Specificity

Question 11

Specificity

Answer 11

Specificity describes the proportion of people without the disease who will have a negative test.

Specificity = d/(b+d)

Question 12

Positive predictive value (PPV)

Answer 12

proportion of people with a positive test who actually have the disease.
PPV varies with prevalence of disease in a population.
The lower the prevalence, the lower the positive predictive value.

PPV = a/(a+b)

Question 13

Negative predictive value

Answer 13

proportion of people with a negative test who truly do not have the disease.

NPV = d/(c+d)

Question 14

False positive rate

Answer 14

The false positive rate is the proportion of those without the condition who will test positive.

False positive rate = 1 - specificity

False negative rate = 1 - d/(b+d)

Question 15

False negative rate

Answer 15

The false negative rate is the proportion of those with the condition who will test negative.

False negative rate = 1 - sensitivity

False negative rate = 1 - a/(a+c)

Question 16

Absolute risk calculation

Answer 16

ARR = Risk(control group) - Risk(experimental group)

Question 17

Relative risk reduction calculation

Answer 17

RRR = 1 - [Risk(Experimental group) / Risk(Control group)]

Question 18

Absolute risk reduction

Answer 18

difference in the risk between the control group and the experimental group
Explains how integration changes outcomes

Question 19

RISK/PREVALENCE?

Answer 19

probability of an event occurring within a defined population.

Question 20

RISK RATIO (RR)?

Answer 20

probability of an event occurring in an exposed group compared to the probability occurring in a non-exposed group.

Question 21

Interventional study

Answer 21

participants are assigned to groups that receive one or more intervention/treatment
or no intervention
Evaluate the effects of the interventions on biomedical or health-related outcomes.

Question 22

Interventional studies use

Answer 22

answer study questions relating to either therapeutic agents, and evaluating the efficacy of therapeutic agents, or are used to assess mechanisms of preventing potential causes of damage.

Question 23

Measurement bias

Answer 23

error due to data collection during measurement.

systematic error and is therefore retained across the data set.

occur in both qualitative and quantitative studies.

Question 24

Causes of measurement bias in quantitative studies

Answer 24

poor calibration of measuring instruments

experimenter’s eyes not level with equipment

Question 25

Measurement bias in qualitative studies

Answer 25

Participants worried about stigma
Anon response to surveys can reduce this

Question 26

measure of association

Answer 26

quantifies the relationship between exposure and outcome.

Question 27

Type 1 error

Answer 27

false positive
Incorrect rejection of null hypothesis

Question 28

Type 2 error

Answer 28

false negative
failure to reject then null hypothesis when it is false.

Question 29

Sampling bias

Answer 29

non-random sample of a population

Question 30

TIME INTERVAL BIAS

Answer 30

Early termination of a trial at a time when its results support a desired conclusion

Question 31

SUSCEPTIBILITY BIAS

Question 32

ATTRITION BIAS

Answer 32

attrition or loss of participants, discounting trial subjects/tests that did not run to completion.

Question 33

Intention to test analysis

Answer 33

avoid the effects of crossover and dropout, which may break the random assignment to the treatment groups in a study