exam ii: ch9

Question 1

defines the selected group of people or elements from which data are collected for a study

Answer 1

sample

Question 2

an entire set of individuals or elements who meet the sampling criteria

Answer 2

target population

Question 3

portion of the target population to which the researcher has reasonable access

Answer 3

accessible population

Question 4

individual units of the population and sample

Answer 4

elements

Question 5

extending the findings from the sample under study to the larger population
- Influenced by quality and consistency of study

Answer 5

generalization

Question 6

characteristics that the subject/element must possess to be part of the target population

Answer 6

inclusion criteria

Question 7

characteristics that can cause a person/element to be excluded from the target population

Answer 7

exclusion criteria

Question 8

as similar as possible to control for extraneous variables

Answer 8

homogenous sample

Question 9

represents a broad range of values

Answer 9

heterogenous sample

Question 10

the sample, accessible, and target populations are alike in as many ways as possible
- May be evaluated in terms of the setting, characteristics of the participants, number of participants in a study

Answer 10

representativeness

Question 11

the difference between the population mean and the mean of the sample
- Want the mean to be as close as possible
- Probability of error increases when the sampling process is not random

Answer 11

sampling error

Question 12

expected difference in values that occurs when different subjects from the same sample are examined

Answer 12

random variation

Question 13

consequence of selecting subjects whose measurement values differ in some way from those of the population

Answer 13

systematic variation/systemic bias

Question 14

% of subjects who declined to participate in the study

Answer 14

refusal rate

Question 15

how to calculate refusal rate?

Answer 15

If 80 approached, 4 refused
4/80 = 0.05 x 100 = 5% refusal rate (good!)

Question 16

% of subjects who consented to be in the study

Answer 16

acceptance rate

Question 17

how to calculate acceptance rate?

Answer 17

80 approached and 76 accepted
76/80 = 0.95 x100 = 95% acceptance rate (good!)

Question 18

withdrawal or loss of subjects from a study

Answer 18

sample attrition

Question 19

how to calculate sample attrition?

Answer 19

of subjects withdrawing/number of subjects x 100

Question 20

number of subjects who remain in and complete a study

Answer 20

sample retention

Question 21

type of sampling that increases the representativeness of the sample based on the target population

Answer 21

random sampling

Question 22

what is the difference between control group vs comparison group?

Answer 22

control: used in studies with random sampling
comparison: not randomly determined

Question 23

a listing of every member of the population, using the sampling criteria to define membership in the population

Answer 23

sampling frame

Question 24

outlines strategies used to obtain sample for a study

Answer 24

sampling plan

Question 25

type of sampling in which each person/element in population has an opportunity to be selected for a sample (random sampling)

Answer 25

probability sampling plans

Question 26

type of sampling in which not every element of a population has the opportunity to be selected for study sample

Answer 26

nonprobability sampling plans

Question 27

type of probability sampling that is achieved by randomly selecting elements from the sampling frame

Answer 27

simple random sampling

Question 28

type of probability sampling that is used in situations in which the researcher knows some of the variables in the population that are critical for achieving representativeness.

Answer 28

stratified random sampling

Question 29

type of probability sampling in which a researcher develops a sampling frame that includes a list of all the states, cities, institutions, or clinicians with which elements of the identified population can be linked

Answer 29

cluster sampling

Question 30

type of probability sampling when an ordered list of all members of the population is available

Answer 30

systematic sampling

Question 31

simple random sampling, stratified random, cluster, systematic sampling

Answer 31

types of probability sampling

Question 32

type of nonprobability sampling; accidental sampling, inexpensive, accessible, usually less time consuming to obtain

Answer 32

convenience sampling

Question 33

type of nonprobability sampling that shares a similar technique to convenience BUT adds strategy to ensure the inclusion of participant types that are likely to be underrepresented in the convenience

Answer 33

quota sampling

Question 34

type of nonprobability sampling in which efforts are made to include typical/atypical subjects - Based on researcher’s judgment

Answer 34

purposeful sampling

Question 35

type of nonprobability sampling that takes adv of social networks to get the sample - One person in sample asks another to join, so on

Answer 35

network sampling (snowball sampling)

Question 36

type of nonprobability sampling that is used in grounded theory research; data are gathered from any individual/group that can provide relevant data for theory generation - sample is saturated when data collection is complete (per researcher's judgement)

Answer 36

theoretical sampling

Question 37

convenience, quota, purposeful, network, theoretical sampling

Answer 37

types of nonprobability sampling

Question 38

the ability of the study to detect differences or relationships that actually exist in the population

Answer 38

powr

Question 39

the ability to detect differences in the population or capacity to correctly reject a null hypothesis - standard power = - types of level of significance?

Answer 39

power analysis - standard power = 8 - levels of significance (alpha 0.05, 0.01, 0.001)

Question 40

what is the most common power analysis/level of significance?

Answer 40

alpha = 0.05

Question 41

the presence of the phenomenon; extent to which null hypothesis is false - Increased sample size = increase variability = increased effect size

Answer 41

effect size

Question 42

concept that asks if the tool used a reliable and valid measure of the variable

Answer 42

measurement sensitivity

Question 43

anova, t-test, chi-square

Answer 43

types of data analysis techniques

Question 44

explain the following research settings - natural - partially controlled - highly controlled

Answer 44

- natural: uncontrolled, real life situation/environment - partially controlled: an environment that is manipulated/modified in some way by the researcher - highly controlled: environmentally structured for the purpose of conductive research (lab)

Question 45

what is the difficulty with longitudinal studies?

Answer 45

subject attrition and maturation = can affect outcomes

Question 46

descriptive, correlational, and outcomes need _____ samples

Answer 46

large samples

Question 47

quasi and experimental need ____ samples - and why?

Answer 47

smaller samples bc need higher control

Question 48

what is the weakest technique for data analysis?

Answer 48

chi square bc needs a large sample size to achieve acceptable levels of power

Question 49

as the # of categories increases, the sample size must _____

Answer 49

increase

Question 50

what type of sampling is mostly implemented in grounded theory research?

Answer 50

theoretical sampling