class 10

Question 1

target population

Answer 1

selecting a group of people, events, or behvaiours, or other elements with which to conduct a study

Question 2

element (aka case)

Answer 2

an individual unit of a population:
-person(subject)
-event
-behaviour

Question 3

sample

Answer 3

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

Question 4

target population

Answer 4

the entire set of indviudals (or elements) that met the sampling criteria (the P in PICO)

Question 5

“PICO”

Answer 5

P-population
I-intervention of influence
C-comparison
O-outcome

Question 6

target population

Answer 6

group to whom the researcher aims to generalize transfer/findings

Question 7

accessible population

Answer 7

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

Question 8

generalizability

Answer 8

the degree to which data are representative of similar phenomena in a population beyond the studied sample

Question 9

representativeness

Answer 9

-key characteristics of the sample are similar to those of the population
-sample,accessible,population, and the target population are alike in as many ways as possible

Question 10

representativenes needs to evaluate:

Answer 10

-setting
-characteristics of the subjects: age, gender, ethnicity,income, education
-distribution of values of variables

Question 11

homogenity

Answer 11

degree to which subjects are similar

Question 12

heterogeneity

Answer 12

degree to which subjects are different

Question 13

what do homogeneity and heterogeneity impact

Answer 13

representativeness and generalizability

Question 14

what is sampling criteria

Answer 14

the characteristics essential for inclusion in the target population
-consist of: inclusion (eligibility) criteria and exclusion criteria (delimitations)

Question 15

sampling criteria examples

Answer 15

i.e. between the ages of 18 and 45, ability to speak english, diagnosed with diabetes in the last month

Question 16

sampling error

Answer 16

-when the value of a statistic fluctuates from one sample to another drawn from the population
i.e. difference between the population mean & the mean of the sample
example: study looking at hairloss, ages 18-65 specified

Question 17

sampling frame

Answer 17

-a listing of every member of the population, using the sampling criteria to define membership in the population
-subjects are selected from the sampling frame

Question 18

sampling plan

Answer 18

outlines strategies used to obtain a sample (who, where, when, how)
ex: sample will randomly chosen from all patients with the diagnosis of subarachnoid hemorrhage in the past 10 years

Question 19

probability (random) sampling

Answer 19

random selection methods
-every individual in the population should have an opportunity to be selected for the sample
-advantage: increases respresentativness
-disadvantage: limited feasibility

Question 20

nonprobability sampling

Answer 20

nonrandom methods

Question 21

probability sampling (simple):

Answer 21

-elements selected randomly from sampling frame (using computer software, number table, drawing names)

Question 22

probability sampling (stratified):

Answer 22

-used when certain variables are considered critical to representativness (e.g. age, gender, geographic location)
-elements organized into strata - random selection from each stratum

Question 23

probability sampling (cluster):

Answer 23

-elements drawn from chosen “mini-representations” or the target population (e.g. cities, provinces)
-can occur in one stage or multiple stages

Question 24

probability sampling (systematic):

Answer 24

-selecting every nth element from a complete list of the population using a random start point

Question 25

nonprobability (nonrandom) sampling:

Answer 25

-not every element in the population has an opportunity to be included in the sample

Question 26

advantage of nonprobability (nonrandom) sampling:

Answer 26

increased feasibility (compared with random sampling) in healthcare research

Question 27

disadvantage of nonprobability (nonrandom) sampling:

Answer 27

increased likelihood of obtaining a non-representative sample

Question 28

nonprobability (nonrandom) sampling (convenience):

Answer 28

-elements are enrolled based on availability
-researcher enrolls until desired sample size is achieved

Question 29

nonprobability (nonrandom) sampling (quota):

Answer 29

-similar to stratified sampling, but inital sample is not random

Question 30

nonprobability (nonrandom) sampling (network (snowball)):

Answer 30

-initial subjects are enrolled by convenience, then additonal subjects are identified through association (e.g. friends, colleagues)

Question 31

nonprobability (nonrandom) sampling (purposive):

Answer 31

-researcher selects subjects based on judgement about who will provide the most useful data to answer the research question

Question 32

factors that influence sample size

Answer 32

-power
-effect size
-type of study conducted
-number of variables
-measurement sensitivity
-data analysis techniques
-frequency of the phenomenon
-cost

Question 33

power

Answer 33

0.80 is minimal acceptable power level
-capacity of the study to detect actual differences aka capacity of the study to correctly reject the null hypothesis
-# of participants needed to avoid a type ii error in a comparative study

Question 34

effect size

Answer 34

a statistical expression of the magnitude of the relationship between two variables or the difference between two groups
-0.2=small effect->larger sample needed
-0.5=medium effect
-0.8=large effect->smaller sample adequate

Question 35

power analysis

Answer 35

-standard power of 0.8
-lvl of significance=0.05,0.01,0.001
-effect size=0.2 small, 0.5 medium, 0.8 large