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| 6327592313 | What is sampling? | A sample is a subset taken from the target population (population of interest) | 0 | |
| 6327687741 | population | The population shares common characteristics that you, the researcher, define before your study begins. | 1 | |
| 6327695511 | target population | Target population is the group from which you can select a sample (from the population you have defined) | 2 | |
| 6327786747 | Sampling Plan | How you put it all together and follow through with design - Qualitative, Quantitative? | 3 | |
| 6327704845 | Quantitative Sampling (usually probability) | • Sample determines external validity (can you generalize your findings from the sample to the population (hopefully) • And to some extent, internal validity (can you rule out all other alternative explanations for the results | 4 | |
| 6327719955 | Steps in Sampling | • Define the population • Develop a plan - how you will select a sample • Determine the size • Select the sample • Compare if the sample truly represents the characteristics of the population. | 5 | |
| 6327888553 | power analysis | used to calculate the minimum sample size required so that one can be reasonably likely to detect an effect of a given size | 6 | |
| 6327730378 | Probability Sampling (usually for quantitative) | • Everyone has an equal chance of being selected • Random - one step do it all • Systematic - select from pre-set intervals • Stratified -fixed % randomly drawn from pre-divided subgroups • Cluster - randomly, sequentially drawn from already existing larger subgroups | 7 | |
| 6327742451 | Examples of Clustering | • Random - assign each individual a number and choose the numbers from a pile of numbers. • Systematic - assign each individual a number and choose odd numbers • Stratified - Determine % of patients that are male or female and choose those % in your sample | 8 | |
| 6327754381 | Non-Probability Sampling (usually for qualitative) | • Do not know the parameters of the population therefore use non-random methods of selection • Convenience-what is available • Purposive-particular characteristics that fit your criteria but non-random • Snowball- word of mouth networking • Quota- set number of subgroups according to the population characteristics but non-randomly | 9 | |
| 6327761960 | Relation of Sampling to Validity | • External validity means that you can accurately generalize the findings from your sample the population. • If the selection of the participants is biased then the results of the study cannot be generalized to a larger population. • Selective effects (error in sampling and selection) is a threat to external validity. | 10 | |
| 6327768835 | Qualitative Sampling (usually non-probability) | • Is purposive - choose those who can offer the most relevant information about your topic • Typically, establish criteria or what you want to include then find participants who fit the bill | 11 | |
| 6327776950 | Boundary Setting | Can choose a sample and further bound the study by choosing: setting, stories, groups, images, experiences, concepts, objects | 12 | |
| 6327818978 | Sampling - Qualitative Characteristics | • Typical- the majority • Extreme or deviant- most extreme to compare to the majority • Comprehensive/Maximum Variation-all the participants or cases that match the criteria are included • Confirming or Disconfirming • Reputational- recommended by experts • Comparable- select cases with the same characteristics that match the criteria over a period of time. • Convenience- can be included most quickly or conveniently | 13 | |
| 6327820886 | Sampling size, what is reasonable? | Quantitative - large size, minimum 30 per variable, but do POWER analysis to confirm sample is large enough Qualitative - small size, 3-5, or single subject | 14 | |
| 6328056026 | Saturation | qualitative - you've interviewed so many people that you start to get no new info | 15 | |
| 6327842676 | Why is theory important in quantitative research? | Guides your decisions: problem statement, which variables to measure, setting boundaries, data collection, analysis, But HELPS TO SEE THE BIG PICTURE | 16 | |
| 6327846538 | Why is theory important in qualitative research? | develop a theory, interpret data | 17 | |
| 6327874987 | what is theory? | • Inter-related concepts (observation), constructs (surmised, categories), relationships, propositions (statements that govern the relationships, suggestions) that can explain or predict human experience - and make it orderly. • Deductive- verify or refute • Inductive- explain, develop | 18 |
