1、Designation: D 5791 95 (Reapproved 2006)Standard Guide forUsing Probability Sampling Methods in Studies of Indoor AirQuality in Buildings1This standard is issued under the fixed designation D 5791; the number immediately following the designation indicates the year oforiginal adoption or, in the cas
2、e of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon (e) indicates an editorial change since the last revision or reapproval.1. Scope1.1 This guide covers criteria for determining when prob-ability sampling methods should be us
3、ed to select locations forplacement of environmental monitoring equipment in a build-ing or to select a sample of building occupants for question-naire administration for a study of indoor air quality. Some ofthe basic probability sampling methods that are applicable forthese types of studies are in
4、troduced.1.2 Probability sampling refers to statistical sampling meth-ods that select units for observation with known probabilities(including probabilities equal to one for a census) so thatstatistically defensible inferences are supported from thesample to the entire population of units that had a
5、 positiveprobability of being selected into the sample.1.3 This guide describes those situations in which probabil-ity sampling methods are needed for a scientific study of theindoor air quality in a building. For those situations for whichprobability sampling methods are recommended, guidance ispro
6、vided on how to implement probability sampling methods,including obstacles that may arise. Examples of their applica-tion are provided for selected situations. Because some indoorair quality investigations may require application of complex,multistage, survey sampling procedures and because this sta
7、n-dard is a guide rather than a practice, the references inAppendix X1 are recommended for guidance on appropriateprobability sampling methods, rather than including exposi-tions of such methods in this guide.2. Referenced Documents2.1 ASTM Standards:2D 1356 Terminology Relating to Sampling and Anal
8、ysis ofAtmospheres3. Terminology3.1 DefinitionsFor definitions of terms used in this guide,refer to Terminology D 1356.3.2 Definitions of Terms Specific to This Standard:3.2.1 censussurvey of all elements of the target popula-tion.3.2.2 cluster samplea sample in which the samplingframe is partitione
9、d into disjoint subsets called clusters and asample of the clusters is selected.3.2.2.1 DiscussionData may be collected for all units ineach sample cluster or, when a multistage sample is beingselected, the units within the sampled clusters may be furthersubsampled.3.2.3 compositing samplesphysicall
10、y combining the ma-terial collected in two or more environmental samples.3.2.4 expected valuethe average value of a sample statis-tic over all possible samples that could be selected using aspecified sample selection procedure.3.2.5 multistage samplea sample selected in stages suchthat larger units
11、are selected at the first stage, and smaller unitsare selected at each subsequent stage from within the unitsselected at the previous stage of sampling.3.2.5.1 DiscussionFor assessing the indoor air quality in apopulation of office buildings, individual buildings might beselected at the first stage
12、of sampling, floors selected withinsample buildings at the second stage, and monitoring locations(for example, rooms or grid points) selected on sampled floorsat the third stage.3.2.6 population parametera characteristic based on orcalculated from all units in the target population.3.2.6.1 Discussio
13、nThe purpose of selecting a sample isusually to estimate population parameters. Population param-eters cannot actually be calculated unless data are available forall units in the population.3.2.7 probability samplea sample for which every unit onthe sampling frame has a known, positive probability o
14、f beingselected into the sample.3.2.7.1 DiscussionThe terms probability sampling andrandom sampling are sometimes used interchangeably.1This guide is under the jurisdiction of ASTM Committee D22 on Air Qualityand is the direct responsibility of Subcommittee D22.05 on Indoor Air.Current edition appro
15、ved Oct. 1, 2006. Published October 2006. Originallyapproved in 1995. Last previous edition approved in 2001 as D 5791 - 95 (2001).2For referenced ASTM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume informa
16、tion, refer to the standards Document Summary page onthe ASTM website.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.3.2.8 sampling framea list from which a sample is se-lected.3.2.8.1 DiscussionAn ideal sampling frame contains each
17、member of the target population exactly once and contains nounits that are not members of the target population. In practice,the sampling frame may miss some members of the targetpopulation (for example, new employees in a building) andinclude some individuals who are not members of the targetpopula
18、tion (for example, individuals who no longer work in thebuilding). However, no member of the population should belisted more than once on the sampling frame.3.2.9 simple random samplea sample of n elements se-lected from the sampling frame in such a way that all possiblesamples of n elements have th
19、e same chance of being selected.3.2.10 statistica sample-based estimate of a populationparameter.3.2.11 stratified samplea sample in which the samplingframe is partitioned into disjoint subsets called strata, andsample units are selected independently from each stratum,possibly at different sampling
20、 rates.3.2.12 systematic samplea sample selected by choosingone of the first k elements on the sampling frame at random andthen including every kth element thereafter.3.2.13 target populationthe set of units or elements (forexample, people or locations in space and time) about which asample is desig
21、ned to provide inferences.3.2.13.1 DiscussionThe target population is sometimesreferred to as the population or universe of interest.3.2.14 unbiased estimatora statistic whose expectedvalue is equal to the population parameter that it is intended toestimate.4. Summary of Guide4.1 When the objectives
22、 of an investigation of indoor airquality include extending inferences from a sample of units tothe larger population from which those units were selected,probability sampling methods must be used to select thesample units to be observed and measured. Examples include:4.1.1 Estimating the distributi
23、ons of health and comfortsymptoms experienced by the employees in a particular build-ing during a specific week.4.1.2 Estimating the distribution of hourly average concen-trations of specific substances in the breathing zone air in aparticular building during the working hours of a specificweek.4.1.
24、3 Estimating the relationship between measures of en-vironmental conditions in a building and the health or comfortsymptoms experienced by the occupants.4.1.4 Thus, the study objectives are always a key consider-ation for determining if probability sampling methods arenecessary. Potential objectives
25、 for indoor air studies that wouldrequire probability sampling methods are discussed explicitlyin Section 6.4.2 Guidance is provided regarding the appropriate prob-ability sampling methods to address these and other goals thatrequire extending inferences from a sample to a specificpopulation. Those
26、sampling methods require construction of asampling frame from which population elements can beselected. 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 effec-tively covers the entire population of interest, and4.2.3 A li
27、st of all persons who work in a specific building.4.3 Since environmental concentrations usually vary con-tinuously in time, spatial frame units like those listed in 4.2often must be crossed with temporal units, such as seasons,weeks, days, or hours, to form sampling frame units (forexample, buildin
28、g-seasons, office-weeks, or person-days). Spe-cific issues that must be considered when constructing thesetypes of sampling frames are discussed in Section 7.4.4 In addition to constructing sampling frames, a random-ization procedure is necessary so that units can be selectedfrom the frame with know
29、n probabilities. Some basic consid-erations for and methods of selecting probability samples forstudies of indoor air quality are presented in Section 8.4.5 Finally, Section 9 discusses considerations for statisticalanalysis and reporting that are peculiar to data collected usingprobability sampling
30、 designs. Special statistical analysis meth-ods are necessary when the sampling design includes stratifi-cation, clustering, multistage sampling, or unequal probabili-ties of selection.5. Significance and Use5.1 Studies of indoor air problems are often iterative innature. A thorough engineering eval
31、uation of a building (1-4)3is sometimes sufficient to identify likely causes of indoor airproblems. When these investigations and subsequent remedialmeasures are not sufficient to solve a problem, more intensiveinvestigations may be necessary.5.2 This guide provides the basis for determining whenpro
32、bability sampling methods are needed to achieve statisti-cally defensible inferences regarding the goals of a study ofindoor air quality. The need for probability sampling methodsin a study of indoor air quality depends on the specificobjectives of the study. Such methods may be needed to selecta sa
33、mple of people to be asked questions, examined medically,or monitored for personal exposures. They may also be neededto select a sample of locations in space and time to bemonitored for environmental contaminants.5.3 This guide identifies several potential obstacles toproper implementation of probab
34、ility sampling methods instudies of indoor air quality in buildings and presents proce-dures that overcome those obstacles or at least minimize theirimpact.5.4 Although this guide specifically addresses samplingpeople or locations across time within a building, it alsoprovides important guidance for
35、 studying populations of build-ings. The guidance in this document is fully applicable tosampling locations to determine environmental quality orsampling people to determine environmental effects withineach building in the sample selected from a larger populationof buildings.3The boldface numbers in
36、 parentheses refer to the list of references at the end ofthis guide.D 5791 95 (2006)26. Study Objectives That Require Probability SamplingMethods6.1 Inferences beyond the units actually observed in asample are not rigorously defensible unless the units observedare a probability sample selected from
37、 the population to whichinferences will be extended. Thus, probability sampling meth-ods are needed whenever inferences will be extended from theunits observed in a sample to a larger population. The need forsuch inferences depends directly on the objectives of the study.The study objectives may inc
38、lude characterizing a buildingsoccupants using a survey, or characterizing a buildings airquality using environmental monitoring, or a combination ofboth.6.2 Occupant Survey:6.2.1 A sample of building occupants may be asked tocomplete a questionnaire or to submit to a physical examina-tion. If the i
39、ntention is to make inferences from the sampleregarding the health and comfort symptoms of all the employ-ees of the building, a census of all building occupants or aprobability sample selected from them is required. The occu-pants would typically be asked about their health and comfortsymptoms for
40、a specific period of time (for example, the daythat the survey is administered, the previous week, month, oryear, and so forth). Developing a valid and reliable question-naire is a complex process and is not directly addressed by thisguide (5).6.2.2 Specific study objectives that require inferences
41、to apopulation of building occupants include the following:6.2.2.1 Estimate the distribution of health and comfortsymptoms in a building either before beginning air qualitymeasurements, after implementing remedial measures, or as ameasure of the magnitude of a potential indoor air problem.6.2.2.2 Es
42、timate the distribution of health and comfortsymptoms in a building with reported problems and in anotherbuilding studied for comparison purposes.6.2.2.3 Estimate the relationship of health and comfortsymptoms with worker characteristics, such as age, sex, worklocation, or type of work performed.6.2
43、.3 When inferences regarding the occupants of a buildingare needed, a census of all the building occupants may benecessary. For example, a census of building occupants may beneeded to establish statistical differences in occupant comfortor health symptoms between different work areas (for example,fl
44、oors) within a building. In other cases (for example, estimat-ing the relative frequency of complaints in a building with alarge number of workers), a probability sample may providesufficient precision at less cost.6.2.4 If the characteristics measured in a questionnaire aretemporally dependent (for
45、 example, comfort and health symp-toms on the day of questionnaire administration), a sample ofpeople and time periods may be needed (for example, a sampleof person-days within a given week). Moreover, the surveymay need to be replicated across time (that is, repeated indifferent seasons).6.2.5 A su
46、ccessful occupant survey requires that a largeportion of the sample subjects complete the survey. The Officeof Management and Budget usually requires 75 % or more forfederally funded surveys. Thus, the success of a survey maydepend upon the burden it imposes, pre-survey publicity (forexample, newsle
47、tters or union endorsements), and follow-up ofnonrespondents. The survey should be conducted in such amanner that people are sufficiently motivated to participate butnot unduly alarmed about a potential air quality problem.Finally, residual nonresponse is inevitable, and survey dataanalysis procedur
48、es that utilize weighting or imputation tocompensate for nonresponse are recommended.6.3 Environmental Monitoring:6.3.1 Since air quality characteristics generally exhibit bothspatial and temporal variability, each air quality measurement(for example, temperature, humidity, or concentrations ofspeci
49、fic substances) is generally representative of a specificlocation and time (or period of time). If the objective is to inferinformation about the distribution of the measured character-istics (for example, the mean or the range) for a targetpopulation of times and places, then probability sampling ofboth locations and times is required to justify that inference.6.3.2 Specific study objectives that require inferences to apopulation of units defined in time and space include thefollowing:6.3.2.1 Estimate the distribution of hourly average concen-trations of specifi
