Sampling

Question 1

Name 3 types of non-probability sampling

Answer 1

1. Judgement
2. convenience
3. purposive → subjects chosen blc they have certain attribute

Question 2

probability sample

Answer 2

each person has a non-zero probability Of being included in study

Question 3

simple Random Sampling

Answer 3

→ sample fixed proportion
→ can be difficult to implement
→ same probability of being picked
→ Random # generator

Question 4

Systematic Random Sampling

Answer 4

1.determine sample size
2. Determine sampling interval by dividing pop Size by sample size
3. Randomly select start point from within first interval
4. sample each person after based on sampling internal
ex. in a pop of 1000 chose every 10th person can also be time- every 12 hours.
→Simple, inexpensive
All units can be counted , calculate internal based on sample size t poprandomly select 1st

Question 5

Stratified Random sampling

Answer 5

1 . total pop is divided Into subgroups Then ppl are randomly selected in each stra

Question 6

Cluster sampling

Answer 6

collection of groups with one or more characteristics in common

1. randomly select# of clusters(primary sampling unit)
2. every person in clusters is sampled( unit of concern)

→ variance btwn groups greater so higher Standard error. ‘ !

Question 7

Multi stage s ampling

Answer 7

similar to cluster sampling G useful if cluster has too many ppl to sample or if ppl in Cluster are too alike

1. Randomly select PSU
2. selected secondary sample
   → to ensure all individuals in pop have some probability select you can do 1 of 2 things:
   a) Select PSU with probability proportional to their size
   ex: if class size is known, larger classes will have a higher probability of being selected → select PSU’s then select fixed# of students to be sampled in each class
   b) if class size is not known, then select a simple random sample of PSU’s then sample a constant proportion of students in each class .

Question 8

what is the multistage sample size calculation based on?

Answer 8

the relative cost of sampling and the between-class variation
if btwn-class variation is high. more classes will need to be sampled.

Question 9

type 1 error

Answer 9

outcomes in groups are declared different when in fact they are not

Question 10

Type 2 error

Answer 10

atcomes in groups being compared are declared not different when in fact they are

Question 11

power

Answer 11

probability of finding a stat sig difference when it exists and is of somemagnitude

Question 12

confidence

Answer 12

degree of certainty that what we have observed is real and not due to chance

Question 13

Allowable error

Answer 13

describes acceptable analytic performance

Question 14

Target population

Answer 14

pop where we extrapolate results to

ex All households in a region

Question 15

source pop

Answer 15

pop where study units are drawn from -→ there should be a conceptual list of all members and non-zero probability of being chosen
ex: households eligible /participating

Question 16

Study pop

Answer 16

All Ppl included in Study

ex: individuals selected to bein study. for which data was recorded

Question 17

Sampling Frame

Answer 17

List of all sampling subjects in source pop (ie from where study subjects are chosen)

Question 18

study weights

Answer 18

Analytical technique to adjust for unequal probability of being selected in a study

Question 19

finite population Correction

Answer 19

used if# of ppl in study group is >10%of source pop
firial variance will be smaller
FPC: N-n /N-1
where N = # in source pop

Question 20

sample size calculation Descriptive studies: means

Answer 20

→ used when primary outcome variable is continuous

Question 21

Sample size calc: proportion

Answer 21

used when primary outcome variable is categorical specifically binary