SOCY 201 - Sampling and Measurement Topics

Multiple Chapters & Lectures

Three Purposes of Research

Exploration, Description, Explanation

Exploration

Approach typically occurs when a researcher examines a ew interest or when the subject of study is relatively new; also appropriate for more persistent phenomena

To satisfy the researcher’s curiosity and desire for better understanding, test the feasibility of undertaking a more extensive study, develop the methods to be employed in any subsequent study

Description

Answer questions of who, what, when, where - researcher observes and then describes what was observed

Explanation

Answer question of how and why - to make plain

Units of Analysis

Object of a study’s interest, the “things” that are the object of a study’s attention

Cases

Specific object to which evidence (data) refers

Units of Observation

The kinds of objects from which evidence is collected - most common unit is people

Individual Data

Evidence gathered about cases that are specific individuals

Aggregate Data

Evidence gathered about cases that are collections of individuals

Social Artifacts

Any product of human activity, each implies a set of objects of the same class

Ecological Fallacy

Reasoning error that occurs when conclusions about individuals are based solely on group observations OR
when we use aggregate data and think that this evidence tells us something about the individuals that compose the aggregate

Exception Fallacy

Reasoning error that occurs when conclusions about aggregates are drawn from individuals

Criteria for Establishing Causality

Variables are correlated, cause occurs before the effect, connection between variables is non spurious

Correlation/Association

Empirical evidence that a change is one variable is systematically identified with a change in another

Nonspuriousness

Are genuine or authentic

Control Variable

Variable identifying the context for the relationship between IV and DV

Necessary Condition

Condition that must be preset for a specific outcome to occur

Sufficient Condition

Condition that, when present, produces a specific outcome

Idiographic Research Viewpoint

Insiders

Nomothetic Research Viewpoint

Outsiders

Analytic Induction

A process for understanding events that relies on grounding concepts in empirical observation and progressively sharpening them through interaction; searching for general isights by systematically looking for patterns among individual cases

Cross-Sectional Study

A study based on observations representing a single point in time

Longitudinal Studies

A study design involving the collection of data at different points in time, designed to permit observations of the same phenomena over an extended period - can be more difficult for quantitative studies

Trend Studies

A type of longitudinal study in which a given characteristic of some population is monitored over time

Cohort Studies

A study in which some specific subpopulation, or cohort, is studied over time, although data may be collected from different members in each set of observations

Panel Studies

A type of longitudinal study in which data is collected from the same set of people at several points in time

Panel Attrition

The increase in participants’ nonresponsiveness over time that reduces the accuracy of longitudinal changes

Conceptualization

The process by which concepts are formed through the selective organization of sensory experience

Reification

Mistake of treating a conceptual construction as something real

Real Definitions

Assume that there is something intrinsic in a thing that leads to its name

Conceptual/Nominal Definitions

Statement that indicates the meaning of an abstract term by expressing it in other abstract terms

Tautology

The thinking error that claims to explain something by referring to itself

Nominal Measures

A variable whose attributes have only the characteristics of being jointly exhaustive and mutually exclusive

Merely offer names or labels for characteristics - like saying I am from SL, only be one

Ordinal Measures

Logically rank-order, describe along some dimension

Can put someone in an order, say that they are more ___ than someone else

Interval Measures

Describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes

When comparing two people using this measure, can say that they are different from each other and one is more __ than the other

Ratio Measures

Describing a variable that has all of the other measures, and a true zero point

Age example - they are different or the same, more than the other, how much they differ, ratio of one to another

Precision

Property that refers to the fineness of measurement distinctions

Accuracy

Property that refers to the correctness of measurements

Test-Retest Method

Making the same measurement more than once

Face Validity

Quality of an indicator that makes it seem a reasonable measure of some variable

Criterion-Related/Predictive Validity

Degree to which a measure relates with some external criterion

Construct Validity

Degree to which a measure relates to other variables as expected within a system of theoretical relationships; based on logical relationships among variables

Content Validity

Degree to which a measure covers the range of meanings included within a concept

Indicators

An empirical specification of some abstract concept

Index

Type of composite measure that combines multiple items that, when aggregated, are intended to represent some more general dimension

Scale

Composed of several items that have a logical or empirical structure among them

Errors

Any difference between reported results and true scores

Census

All the members of a population, includes all the relevant cases in a set

Sample

A selection of members from a population

Random Error

Refers to mistakes that are equally likely to occur

Bias

Error that is sytematic; where some pattern of mistake is more likely than others

Nonprobability Sampling

Any technique in which samples are selected in some fashion not suggested by probability theory - examples are purposive (judgmental), snowball, and quota sampling, as well as reliance on available subjects

Reliance on Available Subjects

Like stopping people at a street corner and asking them to be in the survey, doesn’t allow control over the representativeness of the sample

Purposive or Judgmental Sampling

A type of nonprobability sampling in which you select the units to be observed on the basis of your own judgment about which ones will be the most useful or representative, on the basis of your own knowledge of the population and the purpose of the study

Snowball Sampling

Often used in field research, in which each person interviewed may be asked to suggest additional people for interviewing - appropriate when the members of a special population are difficult to locate - accumulation process, primarily for exploratory purposes

Quota Sampling

Units are selected into the sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied, addresses the issue of representativeness - begins with a matrix or table describing the characteristics of the target population

Quota Frame

Proportions that different cells represent, must be accurate

Informant

Someone well versed in the social phenomenon that you wish to study and who is willing to tell you what they know

Saturation

A sampling principle used in qualitative studies that encourages adding cases until new insights are unlikely

Probability Sampling

The general term for samples selected in accord with probability theory, typically involving some random selection mechanism. Specific types include EPSEM, PPS, simple random sampling, and systematic sampling

Sampling Bias

Systematic error derived from using nonprobability samples that produces unrepresentative results

Representative

Quality of a sample of having the same distribution of characteristics as the population from which it was selected

Equal Probability of Selection Method (EPSEM)

Sample design in which each member of a population has the same chance of being selected into the sample

Sampling Error

Discrepancy between the characteristics of a probability sample and the characteristics of the population

Element

The unit of which a population is composed and which is selected in a sample

Population

The theoretically specified aggregation of the elements in a study

Study Population

That aggregation of elements from which a sample is actually selected

Random Selection

Sampling method in which each element has a equal chance of selection independent of ay other event in the selection process, like flipping a coin

Sampling Unit

Element or set of elements considered for selection in some stage of sampling

Sampling Frame

The list or quasi-list of units that make up a population from which a sample is selected - list of elements making up the population

Simple Random Sampling

a type of probability sampling in which the units composing a population are assigned umbers - set of random numbers is then generated, and the units having those numbers are included in the sample, random number generator ca be used to select elements for the sample

Systematic Sampling

A type of probability sampling in which every kth unit in a list is selected for inclusion in the sample

Sampling Interval

The standard distance (k) between elements selected from a population for a sample

Sampling Ratio

The proportion of elements in the population that are selected to be in a sample

Stratification

Possible modification in the methods of random and systematic sampling, grouping of the units making up a population into homogeneous groups before sampling

Stratified Sampling

Organize the population into homogeneous subsets and to select the appropriate # of elements from each, with heterogeneity between subsets

Cluster Sampling

Multistage sampling approach in which natural groups (clusters) are sampled initially, with the members of each selected group being subsampled afterwards

Potential Errors for Two-Stage Cluster Sample

Initial sample of clusters represents the population of clusters only within a range of sampling error, sample of elements selected within a given cluster represents all the elements in that cluster only within a range of sampling error

Probability Proportionate to Size (PPS) Sampling

Type of multistage cluster sample in which clusters are selected, not with equal probabilities, but with probabilities proportionate to their sizes - as measured by the number of units to be subsampled, each cluster is given a chance of selection proportionate to its size

Weighting

A procedure used in connection with sampling whereby units selected with unequal probabilities are assigned differential weights in such a manner as to make the sample representative of the population from which it was selected