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MC Research part 2
MC Collins from midterm to final
| Question | Answer |
|---|---|
| target population | population for which study outcomes are aimed & which generalizations would like to be made |
| accessible population | the portion of the target population which the researchers has reasonable access |
| sample | selected group of people or elements from which data are collected for a study |
| what is taken from accessible population | sample |
| sampling | selecting a group of people, events, behaviors, or other elements with which to conduct a study |
| element | an individual unit of a population |
| examples of elements | person, event, behaviors |
| sampling criteria | characteristics essential for inclusion in the target population |
| representativeness | sample, the accessible population, and the target population are alike in as many ways as possible |
| need to evaluate what for representativeness | setting, characteristics of the subjects, distribution of values on variables measured in the study |
| simple random sampling | -most basic type -every element has an equal & independent chance of being chosen -sample selected from sampling frame through completely random measures -not subject to bias |
| simple random sampling | - not subject to bias - no guarantee will be representative -ensure differences in the attributes - laborious & inefficient - rarely possible to get complete list |
| stratified random sampling | -population 1st divided into 2 or more strata or subgroups -aim to enhance represetnativeness |
| cluster sampling | multi-stage sampling |
| cluster sampling | - successive random sampling of units ie: - all nursing students - random sample of schools - random sample of students from schools - states, cities, districts, blocks, households |
| systematic sampling | selection of every Kth element from a list or group - determine desired sample size (n) - determine size of population (N) - divide N/n = sampling interval - 1st element selected randomly - essential identical to simple - list arranged randomly no g |
| k =1000/100 = 10 | sampling interval |
| random sampling | equal, independent chance of being selected to participate in the study |
| random assignment | random allocation of subjects to a control or experimental group |
| probability sampling types | - simple random - stratified random - cluster - systematic |
| non-probability sampling | nonrandom |
| non-probability sampling types | - convienience - purposive - network |
| non-probability sampling | - less likely to produce accurate & representative samples - most research samples are this type |
| convenience sampling | - use of conveniently available people or objects meeting study criteria - available subjects maybe atypical of population -stop people on street, run advertisements |
| purposive sampling | -theoretical or judgmental sampling -researcher hand picks subjects -qualitative research -instrument testing -needs assessments |
| network sampling | -early sample members identify & refer others who meet study criteria -specific traits difficult to identify -expedient but has bias |
| factors influencing sample size | effect size, # of variables, homogeneity of the population, attrition, sub-group analysis, measurement sensitivity |
| effect size | an estimate of the magnitude of the relationships between the research variables |
| which need larger samples sizes to detect effect | modest relationships |
| power analysis | review notes about probability of null rejected, level of significance ect. |
| number of variables | the greater number the larger sample size |
| homogeneity of the population | -a small sample may be adequate -greater sampling error when heterogenous -biophysical processes with small amounts of variation may use smaller samples -nursing studies: safer to assume hetero unless prior research or experience contrary |
| attrition | -factor in which determing # of subjects needed -issue for all studies longitudinal -large time periods between data collection -mobile or hard-to-locate population -high risk, vvulnerable, or diable |
| sub-group analysis | -testing hypotheses for specific sub-group of the sample |
| measurement sensitivity | when measuring tool is impercise & susceptible to errors, larger sample sizes are needed to test adequately |
| sampling error definition | differences between population values & sample values |
| sampling error | -impossible to have a perfectly representative sample & 1 that contains no sampling error -probability sampling permits estimates of degree of expected error |
| random variation | expected difference in values that occur when different subjects form the sample sample are examined. difference is random because some values will be higher & others lower than the average population values. |
| systematic variation (bias) | consequence of selecting subjects whose measurement values differ in some specific way from those of the population. these values do not vary randomly around the population mean |
| external validity | extent to which study results can be generalized from the study sample to other subjects, populations, settings, etc. |
| implementing sampling plan | 1. identify target population 2. identify accessible population 3. specify eligibility criteria 4. specify sampling plan 5. recruit the sample |
| recruiting the sample | identify eligible candidates & persuade them to participate. |
| things to keep in mind during recruiting the sample | - face to face vs letter or phone call - manners - recruiter/sample characteristics - persistence - incentives |
| make sure recruits know | -explanation of research benefits -offer summary of results -make participation convenient -study endorsement -assurance of research integrity -document for reasons for non-participation |
Created by:
midnight1854
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