SOC150 LEC 3

systematic review

uses explicit, replicable methods to identify, select, and critically appraise all relevant material

review articles

synthesizes existing research, may or may not follow a strict systematic protocol

ecological fallacy

making claims about individuals based on data from the groups they belong to)

probability sampling

used in quantitative studies)(make precise claims about the broader population, make it generalizable)(do know)(equal chance of being selected)

nonprobability sampling

(qualitative work)(examine the workings of a particular phenomenon and flesh out their theoretical understanding of it)(do not know the likelihood a person in the population will be selected for membership in the sample)

sampling frame

(A list of members of a population that is available to researchers, which they use to select cases for their sample. Ideally, the sampling frame includes every single member of that population)

sampling error

(The difference between the statistics obtained from a sample and the actual parameters of a population.

systematic sampling

A sampling technique where the researcher selects elements from a sampling frame in specified intervals—for instance, every kth element on the list (where the selection interval k is calculated by dividing the total number of population elements by the desired sample size). To allow for an equal chance that every element could be selected, it is also important that the starting point be randomly chosen from within the first k elements on the list.

-periodicity(When a sampling frame exhibits a pattern that occurs at regular intervals, systematic sampling might introduce bias)

stratified sampling

divide the study into two or more mutually exclusive subgroups(strata), then draw a sample from each subgroup(either apply simple random or systematic sampling)

-proportionate stratified sampling(sample sizes for our subgroups match their size in the population)(need at least 30 cases)

-disproportionate stratified sampling(proportions of each subgroup within the sample would not reflect the population)

weighting

adjusting for how much particular cases contribute to the statistics for a sample)(make it more representative)

cluster sampling

A sampling technique in which a researcher begins by sampling groups (or clusters) of population elements and then selects elements from within those groups(efficient method for creating sampling frames)

convenience sampling

draw their samples from a part of the population of interest that is close at hand or otherwise readily available to them(might lead to skewed samples)

snowball sampling

A sampling technique where researchers ask study participants they have already recruited to help identify additional participants.

quota sampling

You create subgroups based on each category and decide on how many people (or other units of analysis) to include from each subgroup. You then collect data from that specified number of cases for each subgroup.

purposive sampling

A nonprobability sampling approach where the selection of cases is guided by the researcher’s theory about what concepts and processes matter

sample for range

(A sampling strategy where the researcher seeks to find a sufficient number of cases that reflect the range of variation across one or more key variables)

iterative sampling

(researchers move back and forth between the process of sampling and the preliminary analysis of data

level of measurement

A classification system that categorizes variables by how their attributes are related to one another)

variables at different levels

variable at nominal level(attributes that are different from one another, do not follow any mathematical order

variable at ordinal level(have attributes that can be ranked using some kind of meaningful comparison)(common in quantitative research)(likert scales, intensity of one's opinion)(importance of ranking)(cannot determine the exact distance between those ranks)

variable of scale level(equal intervals, distance between ranks is equivalent, lying on a continuum)(temperature)

categorical variables

(measured at the two lower levels, nominal and ordinal)

interval measures

(do not have a true zero point)(variables are separated by equal and meaningful distances)

ratio measures

(true zero point

reliability

(consistency of our measures, measure gives the same result when applied repeatedly to the same phenomenon)

test-retest reliability(A method of assessing the reliability of a measure by collecting data from a sample and then retesting the same sample after a period of time)

inter-rater reliability(degree to which different observers agree on what happened)

internal consistency(The degree to which participants’ answers to items within a multiple-item measure are consistent. Specifically, the answers for each item in an index or scale should be correlated with each other, as they all are supposed to measure aspects of the same overall concept)

validity

(measure's accuracy, truthfully reflects the meaning of the concept under study)

face validity(whether it is plausible that the question measures what it intends to measure)(using pilot test measures to test validity)

-content validity(does our chosen measure get at all the important meanings or dimensions of our concept?)

-predictive validity(predicts future phenomena that it should be able to predict, considering the underlying concept it is measuring)

-convergent validity(A method used to assess the validity of a measure by comparing scores on that measure to those derived from an existing measure of the same or a similar concept. A strong correlation between the two measures is evidence that they are both measuring the same thing, and that the new measure is therefore valid in this way)

-discriminant validity(opposite of convergent validity)

measurement error

(the difference between the values of a variable and the true—but unobserved—values of that same variable)(age discrepancy)

systematic error

(measure consistently produces incorrect data, typically in one direction)

acquiescence bias

Bradley effect

(voters did not want to admit that they weren't actually voting for a nonwhite person)

dependability

whether the researcher followed proper procedures in conducting the project. Dependability is a dimension of the larger criterion of trustworthiness)

audit

(A method used to evaluate the rigor of qualitative research by tracing each point made in the published study back to the original data that was its basis)