ASTM D5791-95
(Guide)Standard Guide for Using Probability Sampling Methods in Studies of Indoor Air Quality in Buildings
Standard Guide for Using Probability Sampling Methods in Studies of Indoor Air Quality in Buildings
SCOPE
1.1 This guide covers criteria for determining when probability sampling methods should be used to select locations for placement of environmental monitoring equipment in a building or to select a sample of building occupants for questionnaire administration for a study of indoor air quality. Some of the basic probability sampling methods that are applicable for these types of studies are introduced.
1.2 Probability sampling refers to statistical sampling methods that select units for observation with known probabilities (including probabilities equal to one for a census) so that statistically defensible inferences are supported from the sample to the entire population of units that had a positive probability of being selected into the sample.
1.3 This guide describes those situations in which probability sampling methods are needed for a scientific study of the indoor air quality in a building. For those situations for which probability sampling methods are recommended, guidance is provided on how to implement probability sampling methods, including obstacles that may arise. Examples of their application are provided for selected situations. Because some indoor air quality investigations may require application of complex, multistage, survey sampling procedures and because this standard is a guide rather than a practice, the references in Appendix X1 are recommended for guidance on appropriate probability sampling methods, rather than including expositions of such methods in this guide.
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Designation: D 5791 – 95 An American National Standard
Standard Guide for
Using Probability Sampling Methods in Studies of Indoor Air
Quality in Buildings
This standard is issued under the fixed designation D 5791; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (e) indicates an editorial change since the last revision or reapproval.
1. Scope 3.2.2 cluster sample—a sample in which the sampling
frame is partitioned into disjoint subsets called clusters and a
1.1 This guide covers criteria for determining when prob-
sample of the clusters is selected.
ability sampling methods should be used to select locations for
3.2.2.1 Discussion—Data may be collected for all units in
placement of environmental monitoring equipment in a build-
each sample cluster or, when a multistage sample is being
ing or to select a sample of building occupants for question-
selected, the units within the sampled clusters may be further
naire administration for a study of indoor air quality. Some of
subsampled.
the basic probability sampling methods that are applicable for
3.2.3 compositing samples—physically combining the ma-
these types of studies are introduced.
terial collected in two or more environmental samples.
1.2 Probability sampling refers to statistical sampling meth-
3.2.4 expected value—the average value of a sample statis-
ods that select units for observation with known probabilities
tic over all possible samples that could be selected using a
(including probabilities equal to one for a census) so that
specified sample selection procedure.
statistically defensible inferences are supported from the
3.2.5 multistage sample—a sample selected in stages such
sample to the entire population of units that had a positive
that larger units are selected at the first stage, and smaller units
probability of being selected into the sample.
are selected at each subsequent stage from within the units
1.3 This guide describes those situations in which probabil-
selected at the previous stage of sampling.
ity sampling methods are needed for a scientific study of the
3.2.5.1 Discussion—For assessing the indoor air quality in a
indoor air quality in a building. For those situations for which
population of office buildings, individual buildings might be
probability sampling methods are recommended, guidance is
selected at the first stage of sampling, floors selected within
provided on how to implement probability sampling methods,
sample buildings at the second stage, and monitoring locations
including obstacles that may arise. Examples of their applica-
(for example, rooms or grid points) selected on sampled floors
tion are provided for selected situations. Because some indoor
at the third stage.
air quality investigations may require application of complex,
3.2.6 population parameter—a characteristic based on or
multistage, survey sampling procedures and because this stan-
calculated from all units in the target population.
dard is a guide rather than a practice, the references in
3.2.6.1 Discussion—The purpose of selecting a sample is
Appendix X1 are recommended for guidance on appropriate
usually to estimate population parameters. Population param-
probability sampling methods, rather than including exposi-
eters cannot actually be calculated unless data are available for
tions of such methods in this guide.
all units in the population.
2. Referenced Documents 3.2.7 probability sample—a sample for which every unit on
the sampling frame has a known, positive probability of being
2.1 ASTM Standards:
selected into the sample.
D 1356 Terminology Relating to Sampling and Analysis of
3.2.7.1 Discussion—The terms probability sampling and
Atmospheres
random sampling are sometimes used interchangeably.
3. Terminology
3.2.8 sampling frame—a list from which a sample is se-
lected.
3.1 Definitions—For definitions of terms used in this guide,
3.2.8.1 Discussion—An ideal sampling frame contains each
refer to Terminology D 1356.
member of the target population exactly once and contains no
3.2 Definitions of Terms Specific to This Standard:
units that are not members of the target population. In practice,
3.2.1 census—survey of all elements of the target popula-
the sampling frame may miss some members of the target
tion.
population (for example, new employees in a building) and
include some individuals who are not members of the target
This guide is under the jurisdiction of ASTM Committee D-22 on Sampling and
population (for example, individuals who no longer work in the
Analysis of Atmospheres and is the direct responsibility of Subcommittee D22.05
on Indoor Air. building). However, no member of the population should be
Current edition approved Sept. 10, 1995. Published November 1995.
listed more than once on the sampling frame.
Annual Book of ASTM Standards, Vol 11.03.
Copyright © ASTM, 100 Barr Harbor Drive, West Conshohocken, PA 19428-2959, United States.
D 5791
3.2.9 simple random sample—a sample of n elements se- 4.4 In addition to constructing sampling frames, a random-
lected from the sampling frame in such a way that all possible ization procedure is necessary so that units can be selected
samples of n elements have the same chance of being selected. from the frame with known probabilities. Some basic consid-
3.2.10 statistic—a sample-based estimate of a population erations for and methods of selecting probability samples for
parameter. studies of indoor air quality are presented in Section 8.
3.2.11 stratified sample—a sample in which the sampling 4.5 Finally, Section 9 discusses considerations for statistical
frame is partitioned into disjoint subsets called strata, and analysis and reporting that are peculiar to data collected using
sample units are selected independently from each stratum, probability sampling designs. Special statistical analysis meth-
possibly at different sampling rates. ods are necessary when the sampling design includes stratifi-
3.2.12 systematic sample—a sample selected by choosing cation, clustering, multistage sampling, or unequal probabili-
one of the first k elements on the sampling frame at random and ties of selection.
then including every kth element thereafter.
5. Significance and Use
3.2.13 target population—the set of units or elements (for
5.1 Studies of indoor air problems are often iterative in
example, people or locations in space and time) about which a
nature. A thorough engineering evaluation of a building (1-4)
sample is designed to provide inferences.
is sometimes sufficient to identify likely causes of indoor air
3.2.13.1 Discussion—The target population is sometimes
problems. When these investigations and subsequent remedial
referred to as the population or universe of interest.
measures are not sufficient to solve a problem, more intensive
3.2.14 unbiased estimator—a statistic whose expected
investigations may be necessary.
value is equal to the population parameter that it is intended to
5.2 This guide provides the basis for determining when
estimate.
probability sampling methods are needed to achieve statisti-
4. Summary of Guide
cally defensible inferences regarding the goals of a study of
4.1 When the objectives of an investigation of indoor air indoor air quality. The need for probability sampling methods
in a study of indoor air quality depends on the specific
quality include extending inferences from a sample of units to
the larger population from which those units were selected, objectives of the study. Such methods may be needed to select
a sample of people to be asked questions, examined medically,
probability sampling methods must be used to select the
sample units to be observed and measured. Examples include: or monitored for personal exposures. They may also be needed
to select a sample of locations in space and time to be
4.1.1 Estimating the distributions of health and comfort
symptoms experienced by the employees in a particular build- monitored for environmental contaminants.
5.3 This guide identifies several potential obstacles to
ing during a specific week.
4.1.2 Estimating the distribution of hourly average concen- proper implementation of probability sampling methods in
studies of indoor air quality in buildings and presents proce-
trations of specific substances in the breathing zone air in a
particular building during the working hours of a specific dures that overcome those obstacles or at least minimize their
week. impact.
4.1.3 Estimating the relationship between measures of en- 5.4 Although this guide specifically addresses sampling
vironmental conditions in a building and the health or comfort people or locations across time within a building, it also
symptoms experienced by the occupants. provides important guidance for studying populations of build-
4.1.4 Thus, the study objectives are always a key consider- ings. The guidance in this document is fully applicable to
ation for determining if probability sampling methods are sampling locations to determine environmental quality or
necessary. Potential objectives for indoor air studies that would sampling people to determine environmental effects within
each building in the sample selected from a larger population
require probability sampling methods are discussed explicitly
in Section 6. of buildings.
4.2 Guidance is provided regarding the appropriate prob-
6. Study Objectives That Require Probability Sampling
ability sampling methods to address these and other goals that
Methods
require extending inferences from a sample to a specific
6.1 Inferences beyond the units actually observed in a
population. Those sampling methods require construction of a
sample are not rigorously defensible unless the units observed
sampling frame from which population elements can be
are a probability sample selected from the population to which
selected. Examples include:
inferences will be extended. Thus, probability sampling meth-
4.2.1 A list of all offices or work stations in a building,
ods are needed whenever inferences will be extended from the
4.2.2 A grid of potential monitoring locations that effec-
units observed in a sample to a larger population. The need for
tively covers the entire population of interest, and
such inferences depends directly on the objectives of the study.
4.2.3 A list of all persons who work in a specific building.
The study objectives may include characterizing a building’s
4.3 Since environmental concentrations usually vary con-
occupants using a survey, or characterizing a building’s air
tinuously in time, spatial frame units like those listed in 4.2
quality using environmental monitoring, or a combination of
often must be crossed with temporal units, such as seasons,
both.
weeks, days, or hours, to form sampling frame units (for
example, building-seasons, office-weeks, or person-days). Spe-
cific issues that must be considered when constructing these
The boldface numbers in parentheses refer to the list of references at the end of
types of sampling frames are discussed in Section 7. this guide.
D 5791
6.2 Occupant Survey: location and time (or period of time). If the objective is to infer
information about the distribution of the measured character-
6.2.1 A sample of building occupants may be asked to
istics (for example, the mean or the range) for a target
complete a questionnaire or to submit to a physical examina-
population of times and places, then probability sampling of
tion. If the intention is to make inferences from the sample
both locations and times is required to justify that inference.
regarding the health and comfort symptoms of all the employ-
ees of the building, a census of all building occupants or a 6.3.2 Specific study objectives that require inferences to a
probability sample selected from them is required. The occu-
population of units defined in time and space include the
pants would typically be asked about their health and comfort following:
symptoms for a specific period of time (for example, the day
6.3.2.1 Estimate the distribution of hourly average concen-
that the survey is administered, the previous week, month, or
trations of specific substances in a building during a specified
year, and so forth). Developing a valid and reliable question-
time frame either before or after implementing remedial
naire is a complex process and is not directly addressed by this
measures, or as a measure of the magnitude of a potential
guide (5).
indoor air problem.
6.2.2 Specific study objectives that require inferences to a
6.3.2.2 Estimate the distribution of hourly average concen-
population of building occupants include the following:
trations of specific substances in a building with suspected
6.2.2.1 Estimate the distribution of health and comfort
problems and in another building studied for comparison
symptoms in a building either before beginning air quality
purposes. In each case, the target population would be defined
measurements, after implementing remedial measures, or as a
as a specific set of building locations crossed with a specific set
measure of the magnitude of a potential indoor air problem.
of time points. Inferences to the population would require that
6.2.2.2 Estimate the distribution of health and comfort
data be collected for a probability sample of the population
symptoms in a building with reported problems and in another units.
building studied for comparison purposes.
6.3.3 Temporal variations in air quality must always be
6.2.2.3 Estimate the relationship of health and comfort considered when designing a survey of a building’s air quality.
symptoms with worker characteristics, such as age, sex, work
Periodic variations, such as diurnal, weekday/weekend, and
location, or type of work performed. seasonal effects can be important. Periodic effects may be
6.2.3 When inferences regarding the occupants of a building caused by periodic variation in activity patterns within the
building or environmental factors that affect source strength or
are needed, a census of all the building occupants may be
necessary. For example, a census of building occupants may be ventilation rate. These temporal variations will affect such
sampling design characteristics as the definition of the popu-
needed to establish statistical differences in occupant comfort
or health symptoms between different work areas (for example, lation units and the definition of sample selection strata.
floors) within a building. In other cases (for example, estimat-
6.3.4 For example, if diurnal effects must be estimated, the
ing the relative frequency of complaints in
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