Chapter 5: Sampling and Generalizability

Probability Sampling Methods

Methods in which the probability of selection is known and is not zero (so there is some chance of selecting each element). These methods randomly select elements and have no systematic bias.

Systematic Bias

Overrepresentation or underrepresentation of some population characteristics in a sample resulting from the method used to select the sample; a sample shaped by systematic sampling error is a biased sample.

Nonrespondents

People or other entities who do not participate in a study although they are selected for the sample.

Population

The entire set of individuals or other entities to which study findings are to be generalized.

Elements

The individual members of the population whose characteristics are to be measured.

95% Confidence Interval of the Mean

The interval from $39,037 to $89,977 , with the lower and upper bounds of this interval termed as the confidence limits.

Random Sampling Error (Chance Sampling Error)

Differences between the population and the sample that are due only to chance factors (random error), not to systematic sampling error. Random sampling error may or may not result in an unrepresentative sample. The magnitude of sampling error resulting from chance factors can be estimated statistically.

Sampling Units

Units listed at each stage of a multistage sampling design.

Enumeration Units

Units that contain one or more elements and that are listed in a sampling frame.

Weighting

Used to reduce the lack of representativeness of a sample.

Sampling and Generalizability Learning Objectives

- Distinguish the two foci of sampling theory. - Identify the circumstances the make sampling unnecessary and the reason they re rare. - Identify the relation between the desired sample, the obtained sample, the sampling frame, and sample quality. - Define and distinguish probability and nonprobability sampling. - Define the major types of probability sampling method and indicate when each is preferred. - Explain when nonprobability sampling methods may be preferred. - Describe the concept of sampling error and explain how its size is affected by the number of cases sampled, the heterogeneity of the population, and the fraction of population included in the sample.

Sampling Error 152 Sampling Frame

A list of all elements or other units containing the elements in a population.

Inferential Statistics

A mathematical tool for estimating how likely it is that a statistical result based on data from a random sample is representative of the population from which the sample is assumed to have been selected.

Simple Random Sampling

A method of sampling in which every sample element is selected only on the basis of chance, through a random process.

Replacement Sampling

A method of sampling in which sample elements are returned to the sampling frame after being selected, so they may be sampled again. Random samples may be selected with or without replacement.

Snowball Sampling

A method of sampling in which sample elements are selected as they are identified by successive informants or interviewees. Respondent-driven sampling is a systematic version of snowball sampling that can reduce bias by giving respondents financial incentives to recruit diverse peers.

Systematic Random Sampling

A method of sampling in which sample elements are selected from a list or from sequential files, with every nth element being selected after the first element is selected randomly within the first interval.

Stratified Random Sampling

A method of sampling in which sample elements are selected separately from population strata that are identified in advance by the researcher.

Random Sampling

A method of sampling that relies on a random, or chance, selection method so that every element of the sampling frame has a known probability of being selected.

Cluster

A naturally occurring, mixed aggregate of elements of the population.

Purposive Sampling

A nonprobability sampling method in which elements are selected for a purpose, usually because of their unique position.

Quota Sampling

A nonprobability sampling method in which elements are selected to ensure that the sample represents certain characteristics in proportion to their prevalence in the population.

Representative Sample

A sample that " looks like" the population from which it was selected in all respects that are potentially relevant to the study. The distribution of characteristics among the elements of a representative sample is the same as the distribution of those characteristics among the total population. In an unrepresentative sample, some characteristics are overrepresented or underrepresented.

Probability Sampling Method

A sampling method that relies on a random, or chance, selection method so that the probability of selection of population elements is known.

Periodicity

A sequence of elements (in a list to be sampled) that varies in some regular, periodic pattern.

Target Population

A set of elements larger than or different from the population sampled and to which the researcher would like to generalize study findings.

Sample

A subset of a population that is used to study the population as a whole.

Random Number Table

A table containing lists of numbers that are ordered solely on the basis of chance; it is used for drawing a random sample.

Disproportionate Stratified Cluster Sample

Combination of cluster and stratified probability sampling methods (i.e. Rossi, 1989: blocks classified into strata then picked randomly then interview homeless in these blocks)

Census

Research in which information is obtained through responses from or information about all available members of an entire population.

Disproportionate Stratified Sampling

Sampling in which elements are selected from strata in different proportions from those that appear in the population.

Cluster Sampling

Sampling in which elements are selected in two or more stages, with the first stage being the random selection of naturally occurring clusters and the last stage being the random selection of elements within clusters.

Availability Sampling

Sampling in which elements are selected on the basis of convenience.

Proportionate Stratified Sampling

Sampling method in which elements are selected from strata in exact proportion to their representation in the population.

Nonprobability Sampling Method

Sampling method in which the probability of selection of population elements is unknown.

Probability of Selection

The likelihood that an element will be selected from the population for inclusion in the sample. In a census of all elements of a population, the probability that any particular element will be selected is 1.0. If half the elements in the population are sampled on the basis of chance (say, by tossing a coin), the probability of selection for each element is one half, or.5. As the size of the sample as a proportion of the population decreases, so does the probability of selection.

Sampling Interval

The number of cases from one sampled case to another in a systematic random sample.

Random Digit Dialing

The random dialing by a machine of numbers within designated phone prefixes, which creates a random sample for phone surveys.

Sample Statistic

The value of a statistic, such as a mean, computed from sample data.

Population Parameter

The value of a statistic, such as a mean, computed using the data for the entire population; a sample statistic is an estimate of a population parameter.