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UMass Amherst PUBHLTH 391B - Unit_1Introduction_Sampling

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Slide 1Learning ObjectivesWhat is Biostatistics?Types of BiostatisticsResearch ProcessSlide 6Useful TerminologyOverview on samplingAdvantages of SamplingAdvantages of SamplingAdvantages of SamplingDisadvantages of SamplingSampling bias example: Landon vs. FDRThe Literary Digest PollThe Literary Digest Poll - what went wrong?Bias occurred because two things ocurred:What is a good sample?The Sampling ProcessThe PopulationPopulation definition…….SAMPLING…….The Sampling ProcessSAMPLING FRAMESAMPLING FRAMEPracticeProcessTypes of SamplesPROBABILITY SAMPLINGSIMPLE RANDOM SAMPLINGSIMPLE RANDOM SAMPLINGSTRATIFIED SAMPLINGSTRATIFIED SAMPLING…….STRATIFIED SAMPLINGMULTI-STAGE SAMPLINGEXAMPLE OF MULTI-STAGE SAMPLINGMULTI-STAGE SAMPLINGPracticeSYSTEMATIC SAMPLINGSYSTEMATIC SAMPLING……SYSTEMATIC SAMPLING……SYSTEMATIC SAMPLING……NON PROBABILITY SAMPLINGQUOTA SAMPLINGCONVENIENCE SAMPLINGCONVENIENCE SAMPLINGLIMITATIONS OF NON PROBABILITY SAMPLINGLIMITATIONS OF NON PROBABILITY SAMPLINGPracticePracticeProcessCan any sampling protocol produce a representative sample?Slide 52Slide 53Study DesignsInferencesWhich Design is BestCross-Sectional SurveyCross-Sectional SurveyProspective Cohort StudyCohort StudyCohort StudiesCohort StudiesThe Framingham Heart StudySelection of Study SampleCase-Control StudyCase-Control StudyCase-Control StudiesSamplingFeaturesIssuesRandomized Control TrialRandomized Control TrialRandomized Controlled Trial (Clinical Trial)FeaturesRandom Assignment vs. Random SamplingIntroduction to BiostatisticSlides adpated from Mine Çetinkaya-Rundel of OpenIntroThe slides may be copied, edited, and/or shared via the CC BY-SA licenseLearning Objectives●Define biostatistics and elucidate its role in the research process ●Understand how samples are used to draw conclusions on populations●Distinguish between probability and non-probability sampling●Understand sources of bias resulting from non-probability samplingWhat is Biostatistics?Application of statistical principles to medical, public health and biological applications●Collecting, summarizing, interpreting information and making inferences that appropriately account for uncertaintyTypes of Biostatistics Two types of biostatistics:Descriptive Statistics deal with the enumeration, organization and graphical representation of data from a sampleInferential Statistics deal with reaching conclusions from incomplete information, that is, generalizing from the specific sample Inferential statistics use available information in a sample to draw inferences about the population from which the sample was selectedRahbarResearch ProcessResearch questionHypothesisIdentify research designData collectionPresentation of dataData analysisInterpretation of dataPolgar, Thomas5What Biostatisticians Do!Where do we get data?SamplingSlides developed by Mine Çetinkaya-Rundel of OpenIntroThe slides may be copied, edited, and/or shared via the CC BY-SA licenseSome images may be included under fair use guidelines (educational purposes)Useful TerminologyPopulation: is a class of individualsParameters: are numerical facts about the populationSample: a subset of the populationSampling frame: the list from which potential subjects are drawnStatistics: are numerical factors about the sampleVariable: is something that can varyData: are the values you obtain by measuring variablesOverview on sampling POPULATION(unknown parameter)SampleData from Sample are used to describe or make inferences about PopulationRequire an unbiased sample with minimized sampling errorAdvantages of Sampling1. Sampling makes possible the study of a large, heterogeneous (different characteristics) population.- With a large population it may be almost impossible to reach all of them. Sampling enabes the researcher to reach a small portion of the population.Advantages of Sampling2. Sampling is relatively cheap.- Research without sampling may be too costly. Sampling reduces the study population to a reasonable size, reducing expenses.3. Sampling is relativel fast.- Research without sampling might be too time consuming.Advantages of Sampling4. Sampling provides accuracy.- If it takes too long a time to cover the whole study population, there maybe inaccuracy. The research must be finished within a reasonable period of time so that the data are still true, valid and reasonable.Disadvantages of Sampling1. If sampling is biased, or not representative, or too small, the conclusion may not be valid and reliable.2. If the population is very large and there are many subgroups, the sampling procedure becomes very complicated.3. Sampling may require advanced techinical skill.A historical example of a biased sample yielding misleading resultsSampling bias example:Landon vs. FDRIn 1936, Landon sought the Republican presidential nomination opposing the re-election of FDR.●The Literary Digest polled about 10 million Americans, and got responses from about 2.4 million.●The poll showed that Landon would likely be the overwhelming winner and FDR would get only 43% of the votes.●Election result: FDR won, with 62% of the votes.●The magazine was completely discredited because of the poll, and was soon discontinued.The Literary Digest Poll●The magazine had surveyedoits own readers,oregistered automobile owners, andoregistered telephone users.The Literary Digest Poll -what went wrong?●These groups had incomes well above the national average of the day (remember, this is Great Depression era) which resulted in lists of voters far more likely to support Republicans than a truly typical voter of the time, i.e. the sample was not representative of the American population at the time.1. There was over-sampling of Landon supporters2. The nature of the over-sampling was related to voter preferenceThe sample population was not the same as the population of interest, all American voters!Bias occurred because two things ocurred:What is a good sample? The sample must be valid.●Validity depends on 2 considerations:1. Accuracy – bias is absent from the sample (internal validity)2. Precision – sample represents the population (external validity)The Sampling Process 18The sampling process comprises several stages:1. Defining the population of concern 2. Specifying a sampling frame, a set of items or events possible to measure 3. Specifying a sampling method for selecting items or events from the frame 4. Determining the sample size 5. Implementing the sampling plan 6. Sampling and


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