ASTM D5791-95(2017)
(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
SIGNIFICANCE AND USE
5.1 Studies of indoor air problems are often iterative in nature. A thorough engineering evaluation of a building (1-4)3 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.
5.2 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.
5.3 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.
5.4 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.
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
General Information
Relations
Buy Standard
Standards Content (Sample)
This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the
Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
Designation: D5791 − 95 (Reapproved 2017)
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.
1. Scope 2. Referenced Documents
1.1 This guide covers criteria for determining when prob- 2.1 ASTM Standards:
ability sampling methods should be used to select locations for D1356 Terminology Relating to Sampling and Analysis of
placement of environmental monitoring equipment in a build- Atmospheres
ing or to select a sample of building occupants for question-
naire administration for a study of indoor air quality. Some of 3. Terminology
the basic probability sampling methods that are applicable for
3.1 Definitions—For definitions of terms used in this guide,
these types of studies are introduced.
refer to Terminology D1356.
1.2 Probability sampling refers to statistical sampling meth-
3.2 Definitions of Terms Specific to This Standard:
ods that select units for observation with known probabilities
3.2.1 census, n—survey of all elements of the target popu-
(including probabilities equal to one for a census) so that
lation.
statistically defensible inferences are supported from the
3.2.2 cluster sample, n—a sample in which the sampling
sample to the entire population of units that had a positive
frame is partitioned into disjoint subsets called clusters and a
probability of being selected into the sample.
sample of the clusters is selected.
1.3 This guide describes those situations in which probabil-
3.2.2.1 Discussion—Data may be collected for all units in
ity sampling methods are needed for a scientific study of the
each sample cluster or, when a multistage sample is being
indoor air quality in a building. For those situations for which
selected, the units within the sampled clusters may be further
probability sampling methods are recommended, guidance is
subsampled.
provided on how to implement probability sampling methods,
3.2.3 compositing samples, v—physically combining the
including obstacles that may arise. Examples of their applica-
material collected in two or more environmental samples.
tion are provided for selected situations. Because some indoor
3.2.4 expected value, n—the average value of a sample
air quality investigations may require application of complex,
statistic over all possible samples that could be selected using
multistage, survey sampling procedures and because this stan-
a specified sample selection procedure.
dard is a guide rather than a practice, the references in
Appendix X1 are recommended for guidance on appropriate
3.2.5 multistage sample, n—asampleselectedinstagessuch
probability sampling methods, rather than including exposi- that larger units are selected at the first stage, and smaller units
tions of such methods in this guide.
are selected at each subsequent stage from within the units
selected at the previous stage of sampling.
1.4 Units—The values stated in SI units are to be regarded
3.2.5.1 Discussion—For assessing the indoor air quality in a
as standard. No other units of measurement are included in this
population of office buildings, individual buildings might be
standard.
selected at the first stage of sampling, floors selected within
1.5 This international standard was developed in accor-
sample buildings at the second stage, and monitoring locations
dance with internationally recognized principles on standard-
(for example, rooms or grid points) selected on sampled floors
ization established in the Decision on Principles for the
at the third stage.
Development of International Standards, Guides and Recom-
3.2.6 population parameter, n—a characteristic based on or
mendations issued by the World Trade Organization Technical
calculated from all units in the target population.
Barriers to Trade (TBT) Committee.
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 Oct. 1, 2017. Published October 2017. Originally contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
ɛ1
approved in 1995. Last previous edition approved in 2012 as D5791 – 95 (2012) . Standards volume information, refer to the standard’s Document Summary page on
DOI: 10.1520/D5791-95R17. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D5791 − 95 (2017)
3.2.6.1 Discussion—The purpose of selecting a sample is 4.1.3 Estimating the relationship between measures of en-
usually to estimate population parameters. Population param- vironmental conditions in a building and the health or comfort
eters cannot actually be calculated unless data are available for symptoms experienced by the occupants.
all units in the population. 4.1.4 Thus, the study objectives are always a key consider-
ation for determining if probability sampling methods are
3.2.7 probability sample, n—a sample for which every unit
necessary.Potentialobjectivesforindoorairstudiesthatwould
on the sampling frame has a known, positive probability of
require probability sampling methods are discussed explicitly
being selected into the sample.
in Section 6.
3.2.7.1 Discussion—The terms probability sampling and
4.2 Guidance is provided regarding the appropriate prob-
random sampling are sometimes used interchangeably.
ability sampling methods to address these and other goals that
3.2.8 sampling frame, n—a list from which a sample is
require extending inferences from a sample to a specific
selected.
population. Those sampling methods require construction of a
3.2.8.1 Discussion—An ideal sampling frame contains each
sampling frame from which population elements can be
member of the target population exactly once and contains no
selected. Examples include:
units that are not members of the target population. In practice,
4.2.1 A list of all offices or work stations in a building,
the sampling frame may miss some members of the target
4.2.2 A grid of potential monitoring locations that effec-
population (for example, new employees in a building) and
tively covers the entire population of interest, and
include some individuals who are not members of the target
4.2.3 A list of all persons who work in a specific building.
population(forexample,individualswhonolongerworkinthe
4.3 Since environmental concentrations usually vary con-
building). However, no member of the population should be
tinuously in time, spatial frame units like those listed in 4.2
listed more than once on the sampling frame.
often must be crossed with temporal units, such as seasons,
3.2.9 simple random sample, n—a sample of n elements
weeks, days, or hours, to form sampling frame units (for
selected from the sampling frame in such a way that all
example, building-seasons, office-weeks, or person-days). Spe-
possible samples of n elements have the same chance of being
cific issues that must be considered when constructing these
selected.
types of sampling frames are discussed in Section 7.
3.2.10 statistic, n—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
3.2.11 stratified sample, n—a sample in which the sampling
from the frame with known probabilities. Some basic consid-
frame is partitioned into disjoint subsets called strata, and
erations for and methods of selecting probability samples for
sample units are selected independently from each stratum,
studies of indoor air quality are presented in Section 8.
possibly at different sampling rates.
4.5 Finally, Section 9 discusses considerations for statistical
3.2.12 systematic sample, n—a sample selected by choosing
analysis and reporting that are peculiar to data collected using
oneofthefirst kelementsonthesamplingframeatrandomand probability sampling designs. Special statistical analysis meth-
then including every k th element thereafter.
ods are necessary when the sampling design includes
stratification, clustering, multistage sampling, or unequal prob-
3.2.13 target population, n—thesetofunitsorelements(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, n—a statistic whose expected
is sometimes sufficient to identify likely causes of indoor air
value 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:
objectives of the study. Such methods may be needed to select
4.1.1 Estimating the distributions of health and comfort a sample of people to be asked questions, examined medically,
symptoms experienced by the employees in a particular build- or monitored for personal exposures.They may also be needed
ing during a specific week. to select a sample of locations in space and time to be
monitored for environmental contaminants.
4.1.2 Estimating the distribution of hourly average concen-
trations of specific substances in the breathing zone air in a
particular building during the working hours of a specific
The boldface numbers in parentheses refer to the list of references at the end of
week. this standard.
D5791 − 95 (2017)
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-
toms on the day of questionnaire administration), a sample of
5.4 Although this guide specifically addresses sampling
people and time periods may be needed (for example, a sample
people or locations across time within a building, it also
of person-days within a given week). Moreover, the survey
provides important guidance for studying populations of build-
may need to be replicated across time (that is, repeated in
ings. The guidance in this document is fully applicable to
different seasons).
sampling locations to determine environmental quality or
6.2.5 A successful occupant survey requires that a large
sampling people to determine environmental effects within
portion of the sample subjects complete the survey. For
each building in the sample selected from a larger population
example, the United States Office of Management and Budget
of buildings.
usually requires 75 % or more for federally funded surveys.
Thus, the success of a survey may depend upon the burden it
6. Study Objectives That Require Probability Sampling
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
specific substances) is generally representative of a specific
6.2 Occupant Survey:
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
information about the distribution of the measured character-
complete a questionnaire or to submit to a physical examina-
istics (for example, the mean or the range) for a target
tion. If the intention is to make inferences from the sample
population of times and places, then probability sampling of
regarding the health and comfort symptoms of all the employ-
both locations and times is required to justify that inference.
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
...
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
Designation: D5791 − 95 (Reapproved 2017)
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.
1. Scope 2. Referenced Documents
1.1 This guide covers criteria for determining when prob- 2.1 ASTM Standards:
ability sampling methods should be used to select locations for D1356 Terminology Relating to Sampling and Analysis of
placement of environmental monitoring equipment in a build- Atmospheres
ing or to select a sample of building occupants for question-
naire administration for a study of indoor air quality. Some of 3. Terminology
the basic probability sampling methods that are applicable for
3.1 Definitions—For definitions of terms used in this guide,
these types of studies are introduced.
refer to Terminology D1356.
1.2 Probability sampling refers to statistical sampling meth-
3.2 Definitions of Terms Specific to This Standard:
ods that select units for observation with known probabilities
3.2.1 census, n—survey of all elements of the target popu-
(including probabilities equal to one for a census) so that
lation.
statistically defensible inferences are supported from the
3.2.2 cluster sample, n—a sample in which the sampling
sample to the entire population of units that had a positive
frame is partitioned into disjoint subsets called clusters and a
probability of being selected into the sample.
sample of the clusters is selected.
1.3 This guide describes those situations in which probabil-
3.2.2.1 Discussion—Data may be collected for all units in
ity sampling methods are needed for a scientific study of the
each sample cluster or, when a multistage sample is being
indoor air quality in a building. For those situations for which
selected, the units within the sampled clusters may be further
probability sampling methods are recommended, guidance is
subsampled.
provided on how to implement probability sampling methods,
3.2.3 compositing samples, v—physically combining the
including obstacles that may arise. Examples of their applica-
material collected in two or more environmental samples.
tion are provided for selected situations. Because some indoor
3.2.4 expected value, n—the average value of a sample
air quality investigations may require application of complex,
statistic over all possible samples that could be selected using
multistage, survey sampling procedures and because this stan-
a specified sample selection procedure.
dard is a guide rather than a practice, the references in
Appendix X1 are recommended for guidance on appropriate 3.2.5 multistage sample, n—a sample selected in stages such
probability sampling methods, rather than including exposi-
that larger units are selected at the first stage, and smaller units
tions of such methods in this guide. are selected at each subsequent stage from within the units
selected at the previous stage of sampling.
1.4 Units—The values stated in SI units are to be regarded
3.2.5.1 Discussion—For assessing the indoor air quality in a
as standard. No other units of measurement are included in this
population of office buildings, individual buildings might be
standard.
selected at the first stage of sampling, floors selected within
1.5 This international standard was developed in accor-
sample buildings at the second stage, and monitoring locations
dance with internationally recognized principles on standard-
(for example, rooms or grid points) selected on sampled floors
ization established in the Decision on Principles for the
at the third stage.
Development of International Standards, Guides and Recom-
3.2.6 population parameter, n—a characteristic based on or
mendations issued by the World Trade Organization Technical
calculated from all units in the target population.
Barriers to Trade (TBT) Committee.
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 Oct. 1, 2017. Published October 2017. Originally contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
ɛ1
approved in 1995. Last previous edition approved in 2012 as D5791 – 95 (2012) . Standards volume information, refer to the standard’s Document Summary page on
DOI: 10.1520/D5791-95R17. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D5791 − 95 (2017)
3.2.6.1 Discussion—The purpose of selecting a sample is 4.1.3 Estimating the relationship between measures of en-
usually to estimate population parameters. Population param- vironmental conditions in a building and the health or comfort
eters cannot actually be calculated unless data are available for symptoms experienced by the occupants.
all units in the population. 4.1.4 Thus, the study objectives are always a key consider-
ation for determining if probability sampling methods are
3.2.7 probability sample, n—a sample for which every unit
necessary. Potential objectives for indoor air studies that would
on the sampling frame has a known, positive probability of
require probability sampling methods are discussed explicitly
being selected into the sample.
in Section 6.
3.2.7.1 Discussion—The terms probability sampling and
4.2 Guidance is provided regarding the appropriate prob-
random sampling are sometimes used interchangeably.
ability sampling methods to address these and other goals that
3.2.8 sampling frame, n—a list from which a sample is
require extending inferences from a sample to a specific
selected.
population. Those sampling methods require construction of a
3.2.8.1 Discussion—An ideal sampling frame contains each
sampling frame from which population elements can be
member of the target population exactly once and contains no
selected. Examples include:
units that are not members of the target population. In practice,
4.2.1 A list of all offices or work stations in a building,
the sampling frame may miss some members of the target
4.2.2 A grid of potential monitoring locations that effec-
population (for example, new employees in a building) and
tively covers the entire population of interest, and
include some individuals who are not members of the target
4.2.3 A list of all persons who work in a specific building.
population (for example, individuals who no longer work in the
4.3 Since environmental concentrations usually vary con-
building). However, no member of the population should be
tinuously in time, spatial frame units like those listed in 4.2
listed more than once on the sampling frame.
often must be crossed with temporal units, such as seasons,
3.2.9 simple random sample, n—a sample of n elements
weeks, days, or hours, to form sampling frame units (for
selected from the sampling frame in such a way that all
example, building-seasons, office-weeks, or person-days). Spe-
possible samples of n elements have the same chance of being
cific issues that must be considered when constructing these
selected.
types of sampling frames are discussed in Section 7.
3.2.10 statistic, n—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
3.2.11 stratified sample, n—a sample in which the sampling
from the frame with known probabilities. Some basic consid-
frame is partitioned into disjoint subsets called strata, and
erations for and methods of selecting probability samples for
sample units are selected independently from each stratum,
studies of indoor air quality are presented in Section 8.
possibly at different sampling rates.
4.5 Finally, Section 9 discusses considerations for statistical
3.2.12 systematic sample, n—a sample selected by choosing
analysis and reporting that are peculiar to data collected using
one of the first k elements on the sampling frame at random and
probability sampling designs. Special statistical analysis meth-
then including every k th element thereafter. ods are necessary when the sampling design includes
stratification, clustering, multistage sampling, or unequal prob-
3.2.13 target population, n—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. A thorough engineering evaluation of a building (1-4)
3.2.14 unbiased estimator, n—a statistic whose expected
is sometimes sufficient to identify likely causes of indoor air
value 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:
objectives of the study. Such methods may be needed to select
4.1.1 Estimating the distributions of health and comfort a sample of people to be asked questions, examined medically,
symptoms experienced by the employees in a particular build- or monitored for personal exposures. They may also be needed
ing during a specific week.
to select a sample of locations in space and time to be
monitored for environmental contaminants.
4.1.2 Estimating the distribution of hourly average concen-
trations of specific substances in the breathing zone air in a
particular building during the working hours of a specific 3
The boldface numbers in parentheses refer to the list of references at the end of
week. this standard.
D5791 − 95 (2017)
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-
toms on the day of questionnaire administration), a sample of
5.4 Although this guide specifically addresses sampling
people and time periods may be needed (for example, a sample
people or locations across time within a building, it also
of person-days within a given week). Moreover, the survey
provides important guidance for studying populations of build-
may need to be replicated across time (that is, repeated in
ings. The guidance in this document is fully applicable to
different seasons).
sampling locations to determine environmental quality or
6.2.5 A successful occupant survey requires that a large
sampling people to determine environmental effects within
portion of the sample subjects complete the survey. For
each building in the sample selected from a larger population
example, the United States Office of Management and Budget
of buildings.
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
imposes, pre-survey publicity (for example, newsletters or
Methods
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
specific substances) is generally representative of a specific
6.2 Occupant Survey:
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
information about the distribution of the measured character-
complete a questionnaire or to submit to a physical examina-
istics (for example, the mean or the range) for a target
tion. If the intention is to make inferences from the sample
population of times and places, then probability sampling of
regarding the health and comfort symptoms of all the employ-
both locations and times is required to justify that inference.
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 speci
...
This document is not an ASTM standard and is intended only to provide the user of an ASTM standard an indication of what changes have been made to the previous version. Because
it may not be technically possible to adequately depict all changes accurately, ASTM recommends that users consult prior editions as appropriate. In all cases only the current version
of the standard as published by ASTM is to be considered the official document.
´1
Designation: D5791 − 95 (Reapproved 2012) D5791 − 95 (Reapproved 2017)
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
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.
1.5 This international standard was developed in accordance with internationally recognized principles on standardization
established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued
by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
2. Referenced Documents
2.1 ASTM Standards:
D1356 Terminology Relating to Sampling and Analysis of Atmospheres
3. Terminology
3.1 Definitions—For definitions of terms used in this guide, refer to Terminology D1356.
3.2 Definitions of Terms Specific to This Standard:
3.2.1 census—census, n—survey of all elements of the target population.
3.2.2 cluster sample—sample, n—a sample in which the sampling frame is partitioned into disjoint subsets called clusters and
a sample of the clusters is selected.
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.
Current edition approved April 1, 2012Oct. 1, 2017. Published July 2012October 2017. Originally approved in 1995. Last previous edition approved in 20062012 as
ɛ1
D5791 – 95 (2006).(2012) . DOI: 10.1520/D5791-95R12E01.10.1520/D5791-95R17.
For referenced ASTM standards, visit the ASTM website, www.astm.org, or contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM Standards
volume information, refer to the standard’s Document Summary page on the ASTM website.
3.2.2.1 Discussion—
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D5791 − 95 (2017)
Data may be collected for all units in each sample cluster or, when a multistage sample is being selected, the units within the
sampled clusters may be further subsampled.
3.2.3 compositing samples—samples, v—physically combining the material collected in two or more environmental samples.
3.2.4 expected value—value, n—the average value of a sample statistic over all possible samples that could be selected using
a specified sample selection procedure.
3.2.5 multistage sample—sample, n—a sample selected in stages such that larger units are selected at the first stage, and smaller
units are selected at each subsequent stage from within the units selected at the previous stage of sampling.
3.2.5.1 Discussion—
For assessing the indoor air quality in a population of office buildings, individual buildings might be selected at the first stage of
sampling, floors selected within sample buildings at the second stage, and monitoring locations (for example, rooms or grid points)
selected on sampled floors at the third stage.
3.2.6 population parameter—parameter, n—a characteristic based on or calculated from all units in the target population.
3.2.6.1 Discussion—
The purpose of selecting a sample is usually to estimate population parameters. Population parameters cannot actually be
calculated unless data are available for all units in the population.
3.2.7 probability sample—sample, n—a sample for which every unit on the sampling frame has a known, positive probability
of being selected into the sample.
3.2.7.1 Discussion—
The terms probability sampling and random sampling are sometimes used interchangeably.
3.2.8 sampling frame—frame, n—a list from which a sample is selected.
3.2.8.1 Discussion—
An ideal sampling frame contains each member of the target population exactly once and contains no units that are not members
of the target population. In practice, the sampling frame may miss some members of the target population (for example, new
employees in a building) and include some individuals who are not members of the target population (for example, individuals who
no longer work in the building). However, no member of the population should be listed more than once on the sampling frame.
3.2.9 simple random sample—sample, n—a sample of n elements selected from the sampling frame in such a way that all
possible samples of n elements have the same chance of being selected.
3.2.10 statistic—statistic, n—a sample-based estimate of a population parameter.
3.2.11 stratified sample—sample, n—a sample in which the sampling frame is partitioned into disjoint subsets called strata, and
sample units are selected independently from each stratum, possibly at different sampling rates.
3.2.12 systematic sample—sample, n—a sample selected by choosing one of the first k elements on the sampling frame at
random and then including every k th element thereafter.
3.2.13 target population—population, n—the set of units or elements (for example, people or locations in space and time) about
which a sample is designed to provide inferences.
3.2.13.1 Discussion—
The target population is sometimes referred to as the population or universe of interest.
3.2.14 unbiased estimator—estimator, n—a statistic whose expected value is equal to the population parameter that it is intended
to estimate.
4. Summary of Guide
4.1 When the objectives of an investigation of indoor air quality include extending inferences from a sample of units to the
larger population from which those units were selected, probability sampling methods must be used to select the sample units to
be observed and measured. Examples include:
D5791 − 95 (2017)
4.1.1 Estimating the distributions of health and comfort symptoms experienced by the employees in a particular building during
a specific week.
4.1.2 Estimating the distribution of hourly average concentrations of specific substances in the breathing zone air in a particular
building during the working hours of a specific week.
4.1.3 Estimating the relationship between measures of environmental conditions in a building and the health or comfort
symptoms experienced by the occupants.
4.1.4 Thus, the study objectives are always a key consideration for determining if probability sampling methods are necessary.
Potential objectives for indoor air studies that would require probability sampling methods are discussed explicitly in Section 6.
4.2 Guidance is provided regarding the appropriate probability sampling methods to address these and other goals that require
extending inferences from a sample to a specific population. Those sampling methods require construction of a sampling frame
from which population elements can be selected. Examples include:
4.2.1 A list of all offices or work stations in a building,
4.2.2 A grid of potential monitoring locations that effectively covers the entire population of interest, and
4.2.3 A list of all persons who work in a specific building.
4.3 Since environmental concentrations usually vary continuously in time, spatial frame units like those listed in 4.2 often must
be crossed with temporal units, such as seasons, weeks, days, or hours, to form sampling frame units (for example,
building-seasons, office-weeks, or person-days). Specific issues that must be considered when constructing these types of sampling
frames are discussed in Section 7.
4.4 In addition to constructing sampling frames, a randomization procedure is necessary so that units can be selected from the
frame with known probabilities. Some basic considerations for and methods of selecting probability samples for studies of indoor
air quality are presented in Section 8.
4.5 Finally, Section 9 discusses considerations for statistical analysis and reporting that are peculiar to data collected using
probability sampling designs. Special statistical analysis methods are necessary when the sampling design includes stratification,
clustering, multistage sampling, or unequal probabilities of selection.
5. Significance and Use
5.1 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.
5.2 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.
5.3 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.
5.4 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.
6. Study Objectives That Require Probability Sampling Methods
6.1 Inferences beyond the units actually observed in a sample are not rigorously defensible unless the units observed are a
probability sample selected from the population to which inferences will be extended. Thus, probability sampling methods are
needed whenever inferences will be extended from the units observed in a sample to a larger population. The need for such
inferences depends directly on the objectives of the study. The study objectives may include characterizing a building’s occupants
using a survey, or characterizing a building’s air quality using environmental monitoring, or a combination of both.
6.2 Occupant Survey:
6.2.1 A sample of building occupants may be asked to complete a questionnaire or to submit to a physical examination. If the
intention is to make inferences from the sample regarding the health and comfort symptoms of all the employees of the building,
a census of all building occupants or a probability sample selected from them is required. The occupants would typically be asked
about their health and comfort symptoms for a specific period of time (for example, the day that the survey is administered, the
previous week, month, or year, and so forth). Developing a valid and reliable questionnaire is a complex process and is not directly
addressed by this guide (5).
The boldface numbers in parentheses refer to the list of references at the end of this guide.standard.
D5791 − 95 (2017)
6.2.2 Specific study objectives that require inferences to a population of building occupants include the following:
6.2.2.1 Estimate the distribution of health and comfort symptoms in a building either before beginning air quality
measurements, after implementing remedial measures, or as a measure of the magnitude of a potential indoor air problem.
6.2.2.2 Estimate the distribution of health and comfort symptoms in a building with reported problems and in another building
studied for comparison purposes.
6.2.2.3 Estimate the relationship of health and comfort symptoms with worker characteristics, such as age, sex, work location,
or type of work performed.
6.2.3 When inferences regarding the occupants of a building are needed, a census of all the building occupants may be
necessary. For example, a census of building occupants may be needed to establish statistical differences in occupant comfort or
health symptoms between different work areas (for example, floors) within a building. In other cases (for example, estimating the
relative frequency of complaints in a building with a large number of workers), a probability sample may provide sufficient
precision at less cost.
6.2.4 If the characteristics measured in a questionnaire are temporally dependent (for example, comfort and health symptoms
on the day of questionnaire administration), a sample of people and time periods may be needed (for example, a sample of
person-
...
Questions, Comments and Discussion
Ask us and Technical Secretary will try to provide an answer. You can facilitate discussion about the standard in here.