Standard Guide for Using Probability Sampling Methods in Studies of Indoor Air Quality in Buildings

SIGNIFICANCE AND USE
Studies of indoor air problems are often iterative in nature. A thorough engineering evaluation of a building (1-4) is sometimes sufficient to identify likely causes of indoor air problems. When these investigations and subsequent remedial measures are not sufficient to solve a problem, more intensive investigations may be necessary.
This guide provides the basis for determining when probability sampling methods are needed to achieve statistically defensible inferences regarding the goals of a study of indoor air quality. The need for probability sampling methods in a study of indoor air quality depends on the specific objectives of the study. Such methods may be needed to select a sample of people to be asked questions, examined medically, or monitored for personal exposures. They may also be needed to select a sample of locations in space and time to be monitored for environmental contaminants.
This guide identifies several potential obstacles to proper implementation of probability sampling methods in studies of indoor air quality in buildings and presents procedures that overcome those obstacles or at least minimize their impact.
Although this guide specifically addresses sampling people or locations across time within a building, it also provides important guidance for studying populations of buildings. The guidance in this document is fully applicable to sampling locations to determine environmental quality or sampling people to determine environmental effects within each building in the sample selected from a larger population of 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.
1.4 Units—The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.

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Publication Date
31-Mar-2012
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Drafting Committee
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NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
Contact ASTM International (www.astm.org) for the latest information
´1
Designation: D5791 − 95 (Reapproved 2012)
Standard Guide for
Using Probability Sampling Methods in Studies of Indoor Air
Quality in Buildings
This standard is issued under the fixed designation D5791; 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 (´) indicates an editorial change since the last revision or reapproval.
ε NOTE—Reapproved with editorial changes in April 2012.
1. Scope mendations issued by the World Trade Organization Technical
Barriers to Trade (TBT) Committee.
1.1 This guide covers criteria for determining when prob-
ability sampling methods should be used to select locations for
2. Referenced Documents
placement of environmental monitoring equipment in a build-
ing or to select a sample of building occupants for question-
2.1 ASTM Standards:
naire administration for a study of indoor air quality. Some of
D1356 Terminology Relating to Sampling and Analysis of
the basic probability sampling methods that are applicable for
Atmospheres
these types of studies are introduced.
3. Terminology
1.2 Probability sampling refers to statistical sampling meth-
ods that select units for observation with known probabilities
3.1 Definitions—For definitions of terms used in this guide,
(including probabilities equal to one for a census) so that
refer to Terminology D1356.
statistically defensible inferences are supported from the
3.2 Definitions of Terms Specific to This Standard:
sample to the entire population of units that had a positive
3.2.1 census—survey of all elements of the target popula-
probability of being selected into the sample.
tion.
1.3 This guide describes those situations in which probabil-
3.2.2 cluster sample—asampleinwhichthesamplingframe
ity sampling methods are needed for a scientific study of the
is partitioned into disjoint subsets called clusters and a sample
indoor air quality in a building. For those situations for which
of the clusters is selected.
probability sampling methods are recommended, guidance is
3.2.2.1 Discussion—Data may be collected for all units in
provided on how to implement probability sampling methods,
each sample cluster or, when a multistage sample is being
including obstacles that may arise. Examples of their applica-
selected, the units within the sampled clusters may be further
tion are provided for selected situations. Because some indoor
subsampled.
air quality investigations may require application of complex,
3.2.3 compositing samples—physically combining the ma-
multistage, survey sampling procedures and because this stan-
terial collected in two or more environmental samples.
dard is a guide rather than a practice, the references in
Appendix X1 are recommended for guidance on appropriate
3.2.4 expected value—the average value of a sample statis-
probability sampling methods, rather than including exposi-
tic over all possible samples that could be selected using a
tions of such methods in this guide.
specified sample selection procedure.
1.4 Units—The values stated in SI units are to be regarded 3.2.5 multistage sample—a sample selected in stages such
as standard. No other units of measurement are included in this
that larger units are selected at the first stage, and smaller units
standard. are selected at each subsequent stage from within the units
selected at the previous stage of sampling.
1.5 This international standard was developed in accor-
3.2.5.1 Discussion—For assessing the indoor air quality in a
dance with internationally recognized principles on standard-
population of office buildings, individual buildings might be
ization established in the Decision on Principles for the
selected at the first stage of sampling, floors selected within
Development of International Standards, Guides and Recom-
This guide is under the jurisdiction of ASTM Committee D22 on Air
Quality and is the direct responsibility of Subcommittee D22.05 on Indoor Air. For referenced ASTM standards, visit the ASTM website, www.astm.org, or
Current edition approved April 1, 2012. Published July 2012. Originally contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
approved in 1995. Last previous edition approved in 2006 as D5791 – 95 (2006). Standards volume information, refer to the standard’s Document Summary page on
DOI: 10.1520/D5791-95R12E01. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
´1
D5791 − 95 (2012)
sample buildings at the second stage, and monitoring locations 4.1.2 Estimating the distribution of hourly average concen-
(for example, rooms or grid points) selected on sampled floors trations of specific substances in the breathing zone air in a
at the third stage. particular building during the working hours of a specific
week.
3.2.6 population parameter—a characteristic based on or
4.1.3 Estimating the relationship between measures of en-
calculated from all units in the target population.
vironmental conditions in a building and the health or comfort
3.2.6.1 Discussion—The purpose of selecting a sample is
symptoms experienced by the occupants.
usually to estimate population parameters. Population param-
4.1.4 Thus, the study objectives are always a key consider-
eters cannot actually be calculated unless data are available for
ation for determining if probability sampling methods are
all units in the population.
necessary.Potentialobjectivesforindoorairstudiesthatwould
3.2.7 probability sample—a sample for which every unit on
require probability sampling methods are discussed explicitly
the sampling frame has a known, positive probability of being
in Section 6.
selected into the sample.
4.2 Guidance is provided regarding the appropriate prob-
3.2.7.1 Discussion—The terms probability sampling and
ability sampling methods to address these and other goals that
random sampling are sometimes used interchangeably.
require extending inferences from a sample to a specific
3.2.8 sampling frame—a list from which a sample is se-
population. Those sampling methods require construction of a
lected.
sampling frame from which population elements can be
3.2.8.1 Discussion—An ideal sampling frame contains each
selected. Examples include:
member of the target population exactly once and contains no
4.2.1 A list of all offices or work stations in a building,
units that are not members of the target population. In practice,
4.2.2 A grid of potential monitoring locations that effec-
the sampling frame may miss some members of the target
tively covers the entire population of interest, and
population (for example, new employees in a building) and
4.2.3 A list of all persons who work in a specific building.
include some individuals who are not members of the target
4.3 Since environmental concentrations usually vary con-
population(forexample,individualswhonolongerworkinthe
tinuously in time, spatial frame units like those listed in 4.2
building). However, no member of the population should be
often must be crossed with temporal units, such as seasons,
listed more than once on the sampling frame.
weeks, days, or hours, to form sampling frame units (for
3.2.9 simple random sample—a sample of n elements se-
example, building-seasons, office-weeks, or person-days). Spe-
lected from the sampling frame in such a way that all possible
cific issues that must be considered when constructing these
samples of n elements have the same chance of being selected.
types of sampling frames are discussed in Section 7.
3.2.10 statistic—a sample-based estimate of a population
4.4 In addition to constructing sampling frames, a random-
parameter.
ization procedure is necessary so that units can be selected
from the frame with known probabilities. Some basic consid-
3.2.11 stratified sample—a sample in which the sampling
erations for and methods of selecting probability samples for
frame is partitioned into disjoint subsets called strata, and
studies of indoor air quality are presented in Section 8.
sample units are selected independently from each stratum,
possibly at different sampling rates.
4.5 Finally, Section 9 discusses considerations for statistical
analysis and reporting that are peculiar to data collected using
3.2.12 systematic sample—a sample selected by choosing
probability sampling designs. Special statistical analysis meth-
oneofthefirst kelementsonthesamplingframeatrandomand
ods are necessary when the sampling design includes
then including every k th element thereafter.
stratification, clustering, multistage sampling, or unequal prob-
3.2.13 target population—the set of units or elements (for
abilities of selection.
example, people or locations in space and time) about which a
sample is designed to provide inferences.
5. Significance and Use
3.2.13.1 Discussion—The target population is sometimes
5.1 Studies of indoor air problems are often iterative in
referred to as the population or universe of interest.
nature.Athorough engineering evaluation of a building (1-4)
3.2.14 unbiased estimator—astatisticwhoseexpectedvalue
is sometimes sufficient to identify likely causes of indoor air
is equal to the population parameter that it is intended to
problems. When these investigations and subsequent remedial
estimate.
measures are not sufficient to solve a problem, more intensive
investigations may be necessary.
4. Summary of Guide
5.2 This guide provides the basis for determining when
4.1 When the objectives of an investigation of indoor air
probability sampling methods are needed to achieve statisti-
quality include extending inferences from a sample of units to
cally defensible inferences regarding the goals of a study of
the larger population from which those units were selected,
indoor air quality. The need for probability sampling methods
probability sampling methods must be used to select the
in a study of indoor air quality depends on the specific
sample units to be observed and measured. Examples include:
4.1.1 Estimating the distributions of health and comfort
symptoms experienced by the employees in a particular build-
The boldface numbers in parentheses refer to the list of references at the end of
ing during a specific week. this guide.
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D5791 − 95 (2012)
objectives of the study. Such methods may be needed to select 6.2.3 Wheninferencesregardingtheoccupantsofabuilding
a sample of people to be asked questions, examined medically, are needed, a census of all the building occupants may be
or monitored for personal exposures.They may also be needed necessary.Forexample,acensusofbuildingoccupantsmaybe
to select a sample of locations in space and time to be needed to establish statistical differences in occupant comfort
monitored for environmental contaminants. orhealthsymptomsbetweendifferentworkareas(forexample,
floors) within a building. In other cases (for example, estimat-
5.3 This guide identifies several potential obstacles to
ing the relative frequency of complaints in a building with a
proper implementation of probability sampling methods in
large number of workers), a probability sample may provide
studies of indoor air quality in buildings and presents proce-
sufficient precision at less cost.
dures that overcome those obstacles or at least minimize their
6.2.4 If the characteristics measured in a questionnaire are
impact.
temporally dependent (for example, comfort and health symp-
5.4 Although this guide specifically addresses sampling
toms on the day of questionnaire administration), a sample of
people or locations across time within a building, it also
people and time periods may be needed (for example, a sample
provides important guidance for studying populations of build-
of person-days within a given week). Moreover, the survey
ings. The guidance in this document is fully applicable to
may need to be replicated across time (that is, repeated in
sampling locations to determine environmental quality or
different seasons).
sampling people to determine environmental effects within
6.2.5 A successful occupant survey requires that a large
each building in the sample selected from a larger population
portion of the sample subjects complete the survey. For
of buildings.
example, the United States Office of Management and Budget
usually requires 75 % or more for federally funded surveys.
6. Study Objectives That Require Probability Sampling
Thus, the success of a survey may depend upon the burden it
Methods
imposes, pre-survey publicity (for example, newsletters or
union endorsements), and follow-up of nonrespondents. The
6.1 Inferences beyond the units actually observed in a
survey should be conducted in such a manner that people are
sample are not rigorously defensible unless the units observed
sufficiently motivated to participate but not unduly alarmed
are a probability sample selected from the population to which
about a potential air quality problem. Finally, residual nonre-
inferences will be extended. Thus, probability sampling meth-
sponse is inevitable, and survey data analysis procedures that
ods are needed whenever inferences will be extended from the
utilize weighting or imputation to compensate for nonresponse
units observed in a sample to a larger population. The need for
are recommended.
such inferences depends directly on the objectives of the study.
The study objectives may include characterizing a building’s
6.3 Environmental Monitoring:
occupants using a survey, or characterizing a building’s air
6.3.1 Since air quality characteristics generally exhibit both
quality using environmental monitoring, or a combination of
spatial and temporal variability, each air quality measurement
both.
(for example, temperature, humidity, or concentrations of
6.2 Occupant Survey: specific substances) is generally representative of a specific
location and time (or period of time). If the objective is to infer
6.2.1 A sample of building occupants may be asked to
complete a questionnaire or to submit to a physical examina- information about the distribution of the measured character-
istics (for example, the mean or the range) for a target
tion. If the intention is to make inferences from the sample
regarding the health and comfort symptoms of all the employ- population of times and places, then probability sampling of
both locations and times is required to justify that inference.
ees of the building, a census of all building occupants or a
probability sample selected from them is required. The occu- 6.3.2 Specific study objectives that require inferences to a
pants would typically be asked about their health and comfort populat
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