Miscellaneous

Question 1

central limit theorem

Answer 1

for large data samples, the means of many samples are normally distributed, even if the individual sample is not normally distributed

Question 2

alpha

Answer 2

• how much overlap you are willing to tolerate
• your tolerance for making a type 1 error
• the higher your alpha, the more likely you are to make a type 1 error
• typically 5%
• can be spread over 2 tails or 1 tail (2 is stricter than 1)

Question 3

p value

Answer 3

• probability that your result is due to chance
• want P to be less than or equal to alpha
• the smaller your P value, the less likely your results are due to chance

Question 4

generalizability/external validity

Answer 4

• the degree to which you can extrapolate a sample to your population
• the more exclusive/tighter your inclusion criteria for subjects is, the lower the generalizability
• the looser your criteria for subjects is, the higher your generalizability

Question 5

paired test

Answer 5

• each subject gets the intervention you are testing

- measure value before and after intervention ( each subject acts as their own control)

Question 6

Does standard error apply to population or sample?

Answer 6

population

Question 7

what does 95% confidence interval mean?

Answer 7

• 95% chance that the true population mean is within the mean + or - 2 SE

Question 8

5 steps of hypothesis testing

Answer 8

1) establish hypothesis (Ho, A=B)
2) establish alpha (usually 5%)
3) do the STAT MAGIC
4) compare your p value to alpha
5) reject or fail to reject Ho

Question 9

a false positive is a type ___ error

Answer 9

1 (alpha)

Question 10

a false negative is a type ___ error

Answer 10

2 (beta)

Question 11

when is the likelihood of making a type 1 error at its lowest?

Answer 11

the first time you analyze your data (each time after your chance of type 1 error increases)

Question 12

If you have an intervention that you believe will only slightly differ from the placebo, would you use a large or small sample?

Answer 12

small

• if difference between intervention and placebo is v small, then you want dispersion to be narrow enough to minimize the overlap
• SE= SD/ sqrt(n), so if you increase n (sample size), then you decrease the dispersion of your population data, and therefore decrease the overlap

Question 13

describe the x and y variables of the chi-squared/fischer’s exact test.

Answer 13

• categorical x variable (can have multiple)

- categorical y variable (can have multiple)

Question 14

describe the x and y variables of the correlation test.

Answer 14

• continuous x variable
• continuous y variable
• ALL CONTINUOUS VARIABLES MUST HAVE NORMAL DISTRIBUTION*

Question 15

describe the x and y variables of the t-test and ANOVA tests

Answer 15

• categorical x variable ( 2 for t-test, 3+ for ANOVA)
• continuous y variable
• ALL CONTINUOUS VARIABLES MUST HAVE NORMAL DISTRIBUTION*

Question 16

if your continuous variable does not follow normal distribution, what type of analysis should you use? what kind of graph do you use? what is the statistical test?

Answer 16

• survival analysis
• kaplan meier
• log rank

Question 17

what are two examples of dependent variables that are never normally distributed?

Answer 17

• death (survival)

- length of stay in hospital

Question 18

bonferroni correction

Answer 18

if you are doing multiple analyses, you are increasing the risk of a type 1 error, so to correct it, divide alpha by the number of analyses you are doing and use that as your new alpha value

Question 19

What sample size would be needed if there were a large variance in the outcome variable?

Answer 19

large sample size

Question 20

What size sample would be needed if the investigator want to have a study result that is extremely close to the true population mean?

Answer 20

large sample size

Question 21

What sample size would be needed if the difference that the investigator wanted to be able to detect is extremely large?

Answer 21

small sample size

Question 22

Explain: High tolerance for type I error results in large sample size

Answer 22

large sample size increases the risk of type 1 error
( the more analysis you do, the more likely you are to have a type 1 error, so if you are ok with type 1 errors, you are ok with a larger sample)

Question 23

Explain: Smaller α results in larger sample size in order to detect a difference

Answer 23

• smaller alpha means lower tolerance for type 1 error, so you need larger sample to detect a difference

Question 24

Explain: Paired data results in smaller sample size and with more data points

Answer 24

• paired data results in two data points for each subject, which means you will need less subjects to get the same sample size for an unpaired experiment

Question 25

Explain: Small tolerance for type II error necessitates larger sample size

Answer 25

- power + b error = 1 - power is directly related to increasing sample size - if you increase sample size, you increase power, and therefore decrease likelihood for b error

Question 26

what is the standard Beta value

Answer 26

20%

Question 27

discounting

Answer 27

- economic justification for paying for prevention - there may be a cost today for paying for prevention methods, but it is much less than what you would pay if you ended up getting the condition later down the line and needed treatment

Question 28

theory of planned behavior and theory of reasoned action

Answer 28

- intention is the biggest indicator of behavior change | self efficacy: if you believe you can change you are more likely to change

Question 29

lead time bias

Answer 29

- find a disease early in its progression, which makes you think that finding it early has increased your length of time to live (even though you've done no treatment/ there is no benefit to find it early) - ex: finding you have deadly cancer at 45 vs 50 when you're going to die at 60 makes you think that finding the disease earlier has given you more years to live

Question 30

length time bias

Answer 30

- nonaggressive diseases will be preferentially found by screening because aggressive diseases have shorter asymptomatic periods and will be symptomatic more

Question 31

precaution adoption model

Answer 31

1) unaware 2) unengaged 3 undecided --> 4) decide not to act OR 5) decide to act 6) act 7) maintain

Question 32

social learning theory

Answer 32

patients learn best from their experiences and those around them

Question 33

social cognition theory

Answer 33

patient, environment and behavior all influence each other

Question 34

5 A's of smoking cession

Answer 34

``` ask about tobacco use advise them to quit assess their willingness to quit assist in attempt to quit arrange for followup ```