Statistics

Question 1

Categorical variable

Answer 1

• Subject is placed into categories

- Two possible outcomes (yes/no, male/female)–> dichotomous

Question 2

Ordinal

Answer 2

• Inherent order
• Ranked
• May be summarized by a median value

Question 3

Continuous

Answer 3

• Age, weight, height, lab values

- Means and medians used to summarize

Question 4

Unpaired

Answer 4

• Independent means the values of one group cannot be predicted from the other

Question 5

Paired

Answer 5

• Paired the values of one group may be predicted from the other ( patient measured before and after therapy)

Question 6

1, 2, and 3 standard deviations

Answer 6

68.3, 95.8, and 99.7

Question 7

Standard error of the mean

Answer 7

• Because samples drawn from an underlying population do not each produce the same mean (but tend to cluster around the same value), one much calculate the range of where the true (unknown) population mean lies
• The greater the sample size the smaller the SEM
• Always less than SD

Question 8

Null Hypothesis

Answer 8

There is no relationship between two phenomena

Question 9

Chi Squared

Answer 9

• Also called Pearsons

- Suitable for unpaired categorical date from large samples

Question 10

T test

Answer 10

• Used for continuous data

- Used for comparing two sample means from either independent (non paired T test) or matched (paired T test) samples

Question 11

ANOVA

Answer 11

Used to compare the means of several groups, instead of just two
- Looks at the difference within and between groups

Question 12

Confidence interval

Answer 12

• A range of values that there is a specificed probability that value of a parameter lies within it
• 95 percent CI can be estimated if the mean and the SEm are known
• If it crosses zero–> no good

Question 13

Type I error

Answer 13

• Failing to reject the null hypothesis
• Saying a relationship does except when it doesn’t
• Alpha error set at 0.05

Question 14

Type II error

Answer 14

• Failing to reject the null
• Saying there is no difference when there is a difference
• Beta error (0.2)

Question 15

Which error is better? Type I or Type II

Answer 15

• Type II

Question 16

Absolute risk

Answer 16

• Chance of developing a disease over a time period

Question 17

Absolute risk reduction

Answer 17

• The absolute risks of different exposures can be compared to each other
• Risk of drug A is 15%; risk of drug B is 5%–> 10% risk reduction

Question 18

NNT

Answer 18

The inverse of the absolute risk reduction 1/0.10 = 10

Question 19

Relative risk (risk ratio)

Answer 19

• used to compare risk in two different groups with different risk factors exposures
• Calculated by dividing the absolute risk in the group exposed to the risk factor by the absolute risk in the unexposed group
• RR>1 exposure associated with increased risk of disease
• RR=0 no association
• RR <1 exposure is protective

Question 20

Relative risk reduction

Answer 20

1-RR

- Tells you by how much the exposure reduced or increased the risk

Question 21

Odds ratio

Answer 21

• Used in case control ( no incidence rates).

- Calculated by dividing the odds of exposure among cases by odds of exposure among controls

Question 22

Hazard ratio

Answer 22

• Risk ratio gives you the cumulative risk of a time span, while HR gives you the instantaneous risk at a particular point in time

Question 23

Regression analyses

Answer 23

• One way model in which predictor independent (x) variables are thought to affect the dependent outcome (y) variable but not vice versus
• Linear regression (continuous)
• Logistic regression (categorical)

Question 24

Sensitivity

Answer 24

• Percentage of people with disease who test positive
• TP/TP+FN
• Negative test rules out disease
• SNOUT

Question 25

Specificiity

Answer 25

• Percentage of people with a negative test who don’t have disease
• TN/TN+FP
• Positive test rules in disease
• SPIN

Question 26

Positive predictive value

Answer 26

• Percentage of people who test positive who do have the disease
• TP\TP+FP
• depends on prevalence

Question 27

Negative Predictive value

Answer 27

• Percentage of people who test negative who do not have the disease
• TN\TN+FN

Question 28

LIkelihood ratio

Answer 28

• Evaluates the utility of diagnostic tests
• LR + = sensitivty/1- spec
  = LR- = 1- sensiviity /spec

Question 29

ROC

Answer 29

• Allows visual comparison of the performance of a set of different criteria for a diagnostic or screening test
• The nearer the curve to the left upper corner, the better the test is
• AUC , high number the better

Question 30

Systemic review

Answer 30

• Use explicit methods to perform a thorough lit search and critical appraisal of individual studies
• Prereq to meta analysis

Question 31

Meta analysis

Answer 31

• Stat procedure for synthesizing quantitative results from different studies