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Sampling to Study Sampling to Study Drug UseDrug Use

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Sampling to Study Drug Use: Sampling to Study Drug Use: ObjectivesObjectives

• Describe the principles on whichDescribe the principles on which sampling is based sampling is based

• Identify and describe different sampling Identify and describe different sampling methods methods

• Select a sample of health facilitiesSelect a sample of health facilities from a list using at least two different methods from a list using at least two different methods

• Compare the results of the methodsCompare the results of the methods• Instruct others how to sample for Instruct others how to sample for

drug use studies drug use studies

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What Is Sampling?What Is Sampling?

Sampling is a process Sampling is a process by which we study a by which we study a small part of a small part of a population to make population to make judgments about the judgments about the entire population.entire population.

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Sampling involves selecting a number of Sampling involves selecting a number of units from a defined population.units from a defined population.

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Sampling DefinitionsSampling Definitions

• Sampling UnitSampling Unit- - The thing that is sampled: for example, a person, The thing that is sampled: for example, a person, clinical episode, or health facility clinical episode, or health facility

• Study PopulationStudy Population- - All the sampling units that could possibly be All the sampling units that could possibly be included in the sample included in the sample

• Sampling FrameSampling Frame-- A list of all the available sampling units in the study A list of all the available sampling units in the study populationpopulation

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A Representative SampleA Representative Sample

A representative sample has all the A representative sample has all the important characteristics of the important characteristics of the studystudy population from which it ispopulation from which it is drawn.drawn.

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Sampling MethodsSampling Methods

• Two categories of sampling Two categories of sampling methods:methods: - - Nonprobability sampling Nonprobability sampling - - Probability sampling Probability sampling

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Nonprobability Sampling Nonprobability Sampling MethodsMethods

• Convenience SamplingConvenience Sampling- - Study units available at Study units available at the time of data the time of data collection collection are selected are selected for the samplefor the sample

• Quota SamplingQuota Sampling- - Different categories of Different categories of sample units are sample units are included included until a certain until a certain number has number has been been reached in each reached in each

categorycategory

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Probability Sampling MethodsProbability Sampling Methods

• Simple Random SamplingSimple Random Sampling

• Systematic SamplingSystematic Sampling

• Stratified SamplingStratified Sampling

• Cluster SamplingCluster Sampling

• Multistage SamplingMultistage Sampling

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Simple Random SamplingSimple Random Sampling

• Used in situations where Used in situations where the number of sampling the number of sampling units is relatively smallunits is relatively small

• Process:Process: -- Identify all possible units Identify all possible units available for samplingavailable for sampling - - Decide on the size of the Decide on the size of the samplesample -- Choose units by a lottery Choose units by a lottery methodmethod

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Systematic Sampling withSystematic Sampling withEqual ProbabilityEqual Probability

• Numbered list of all possible unitsNumbered list of all possible units• # units # units desired sample size = sampling interval desired sample size = sampling interval

– For example, to select 20 health centers from a list of 46, the sampling interval is For example, to select 20 health centers from a list of 46, the sampling interval is 46/20 = 2.346/20 = 2.3

• Random # x sampling interval = random startRandom # x sampling interval = random start– For example, if the random number is 0.183, calculate For example, if the random number is 0.183, calculate

0.183 × 2.3 = 0.421, which rounds upward to 10.183 × 2.3 = 0.421, which rounds upward to 1• Round number up to choose sample unitRound number up to choose sample unit• Add sampling interval to random start for subsequent unitsAdd sampling interval to random start for subsequent units

– For example,For example,

0.421 + 2.3 = 2.721 or Facility 30.421 + 2.3 = 2.721 or Facility 32.721 + 2.3 = 5.021 or Facility 62.721 + 2.3 = 5.021 or Facility 65.021 + 2.3 = 7.321 or Facility 8 and so forth5.021 + 2.3 = 7.321 or Facility 8 and so forth

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Systematic Sampling withSystematic Sampling withProbability Proportional To SizeProbability Proportional To Size

• List where the units are sorted in decreasing order by some List where the units are sorted in decreasing order by some measure of size (like population or number of visits)measure of size (like population or number of visits)

• Calculate the cumulative totalCalculate the cumulative total

• Cumulative total Cumulative total sample size = sampling interval sample size = sampling interval

• Random # x sampling interval = random startRandom # x sampling interval = random start

• Choose first unit with cumulative total resultChoose first unit with cumulative total result

• Add sampling interval to previous total for subsequent units.Add sampling interval to previous total for subsequent units.

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Stratified SamplingStratified Sampling

• Used when the sampling frame contains clearly Used when the sampling frame contains clearly different categories (strata)different categories (strata)–For example, For example,

• Urban and rural facilities Urban and rural facilities • Facilities with and without doctors Facilities with and without doctors • Government and mission facilitiesGovernment and mission facilities

• Process:Process:-- Organize the list of sampling units by stratumOrganize the list of sampling units by stratum- - Select units within each stratum using a random Select units within each stratum using a random

method (simple random sampling or systematic method (simple random sampling or systematic sampling)sampling)

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Cluster SamplingCluster Sampling

• Used when, for logistic reasons, it is easier to select Used when, for logistic reasons, it is easier to select sample units in groupssample units in groups

• ProcessProcess- - Select a cluster of sample unitsSelect a cluster of sample units– Example: health center with multiple prescribersExample: health center with multiple prescribers

• Include the entire cluster or select a subsample Include the entire cluster or select a subsample oror Select a random sample unit to start each cluster (a Select a random sample unit to start each cluster (a house, a patient, etc.)house, a patient, etc.)- - Include neighboring sample units until a certain Include neighboring sample units until a certain cluster size is reachedcluster size is reached

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Multistage SamplingMultistage Sampling

• Randomly select primary sampling units at the first stage:Randomly select primary sampling units at the first stage:

– Specific communitiesSpecific communities– Specific health facilitiesSpecific health facilities

• Within the primary sampling units, randomly select the Within the primary sampling units, randomly select the final sampling units at the second stage:final sampling units at the second stage:– Drug use encountersDrug use encounters– PatientsPatients– HouseholdsHouseholds

• Sometimes in complex samples, additional stages are Sometimes in complex samples, additional stages are neededneeded

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Sample SizeSample Size

• The optimal sample size is often a compromise The optimal sample size is often a compromise

between what is statistically between what is statistically Desirable Desirable and what and what

is practically is practically FeasibleFeasible..

In general, a minimum In general, a minimum sample size is 30.sample size is 30.

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Sample SizeSample Size

• Sample sizeSample size 50 50100100200200500500

1000 1000

• Range of ConfidenceRange of Confidence 36 - 64% 36 - 64% 40 - 60% 40 - 60% 43 - 57% 43 - 57% 45 - 55% 45 - 55% 47 - 53% 47 - 53%

Confidence IntervalsConfidence Intervals

If the real figure is 50%If the real figure is 50%

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Conclusion Conclusion

• Principles of sampling should be understood Principles of sampling should be understood by everyone involved in drug use studiesby everyone involved in drug use studies

• Enumerators and supervisors shouldEnumerators and supervisors shouldunderstand that any facility, anyunderstand that any facility, anyprescription, or any patient should have a prescription, or any patient should have a chance to be includedchance to be included

• Make every effort to avoid bias in selecting Make every effort to avoid bias in selecting units for studyunits for study

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Activity 1Activity 1

Sample Selection In this exercise, groups will use the different sampling methods on a real data set to select a sample. The results of the different sampling methods will be compared.