introduction to research design - part 2

Question 1

probability sampling

Answer 1

each member of the population has a known non-zero probability of being selected

Question 2

advantage of simple random sampling

Answer 2

sampling will be representative of the population as a whole

Question 3

disadvantage of simple random sampling

Answer 3

typically impossible to obtain a full list of the population of interest

Question 4

advantage of systematic random sampling

Answer 4

easy to perform, good for fieldwork

Question 5

disadvantage of systematic random sampling

Answer 5

assumes the population homogenous

Question 6

stratified random sampling

Answer 6

population is divided into homogeneous strata, then either simple random sampling or systematic random sampling is applied to the strata to draw individuals from that strata

Question 7

advantage of stratified ransom sampling

Answer 7

enables reliable study of heterogenous populations

Question 8

disadvantage of stratified random sampling

Answer 8

lots of information is needed about the population being sampled, including accurate information on the relative proportions of the strata

Question 9

non-probability sampling

Answer 9

members are selected from the population in some - random manner

Question 10

convenience sampling

Answer 10

interested in getting an inexpensive approximation of the truth

Question 11

advantages of convenience sampling

Answer 11

very simple and easy, helpful in pilot studies, cost-effective

Question 12

disadvantages of convenience sampling

Answer 12

venerable to selection bias, high sampling error, little credibility especially when sample size is not large enough

Question 13

judgement sampling

Answer 13

samples selected based on expert opinion or based on own existing knowledge

Question 14

advantages of judgement sampling

Answer 14

less time consuming, allows researchers to go directly to their target population

Question 15

disadvantage of judgement sampling

Answer 15

prone to research bias

Question 16

quota sampling

Answer 16

researchers look for a specific characteristic in their respondents, and then take a tailored sample that is in proportion to a population of interest

Question 17

advantage of quota sampling

Answer 17

relatively easy to administer, can be performed quickly, cost effective, accounts for population proportions

Question 18

disadvantage of quota sampling

Answer 18

potential sample bias

Question 19

snowball sampling

Answer 19

research participants recruit other participants for the study

Question 20

linear snowball sampling

Answer 20

sample group starts with one individual subject providing information about just one subject and then the chain continues with only one referral from one subject

Question 21

exponential non-discriminative snowball sampling

Answer 21

first subject recruited provides multiple referrals. Each new referral then provides more referrals

Question 22

exponential discriminative

Answer 22

each subject gives multiple referrals, however, only one subject is recruited from each referral

Question 23

advantage of snowball sampling

Answer 23

referrals make it easy and quick to find subjects as they come from reliable source, cost-effective, easy to filter the right population

Question 24

disadvantage of snowball sampling

Answer 24

sampling bias and margin of error, lack of cooperation

Question 25

allocation

Answer 25

sample will need to be divided into groups, each of which will be given a different treatment level of the factor

Question 26

randomisation roles

Answer 26

1. removes the selection bias of the researcher placing favourable subjects into the desired factor groupings
2. helps ensure that the groups being compared both reflect the population they are drawn from

Question 27

random allocation advantage

Answer 27

easy, expect an unbiased estimate of effect

Question 28

disadvantage of random allocation

Answer 28

groups will likely end up unequal in size

Question 29

stratified random allocation

Answer 29

subjects divided into strata before being randomly allocated to the groups

Question 30

variable bias

Answer 30

bias obtained when measuring the variables

Question 31

selection bias

Answer 31

in obtaining our sample or in allocating our samples to our treatment groups

Question 32

misclassification bias

Answer 32

individual is included in the wrong group

Question 33

observer or response bias

Answer 33

act of measuring or classifying a variable changes the outcome of that variable

Question 34

ascertainment bias

Answer 34

occurs when the sample is not drawn from a random sample of the population