Sampling in Medical Research

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Sampling in Medical Research

  1. 1. SAMPLING IN RESEARCH Dr. Kusum Gaur Professor, PSM WHO Fellow IEC
  2. 2. Selection of study population Whole Population Sample Population12/08/2012 Dr. Kusum Gaur 2
  3. 3. What is Sample ?• A sample is a small representative segment of a population• Inferences drawn from a sample are expected to be applicable for the source population12/08/2012 Dr. Kusum Gaur 3
  4. 4. Why do we need a sample? To get inferences applicable to universe with minimum resources12/08/2012 Dr. Kusum Gaur 4
  5. 5. Sample – Qualities Sample is a part of population but it is true representative of whole. Qualities Adequate size Appropriate sampling technique12/08/2012 Dr. Kusum Gaur 5
  6. 6. Factors on which SAMPLE SIZE depend:• Population Factors – Type of information available• Type of study – Type of Data – Type of study design – Type of sampling – Type of Statistical Analysis for outcome needed• Determined values of research by researcher – Power – Significance level 12/08/2012 Dr. Kusum Gaur 6
  7. 7. Power: Ability to detect right answerAlpha Error: Chance to miss right answer
  8. 8. Type of Data & level of Measurements Qualitative – Counted Facts – Nominal Data Measured as Numbers expressed as proportions Quantitative- Measured Facts - Numerical Data Measured as quantity & expressed as Mean SD *Ordinal Data – Rank Order Data Measured as rank & expressed as Median Percentile12/08/2012 Dr. Kusum Gaur 13
  9. 9. Sample size for Qualitative data Z 2 PQ 4 PQ Sample Size= ------------------- -- = ------------------ L2 L2 P= Prevalence of disease Q = 100-P L = allowable error Z= 1.96 ≈ 2 for 95% CL for descriptive/case-series type of study design09/03/2010 Dr. Kusum Gaur 14
  10. 10. Sample size for Quantitative data Z 2 SD 2 4 SD 2 Sample Size= ------------------- -- =---------------------- L2 L2 SD= Standard Deviation L = allowable error Z= 1.96 ≈ 2 for 95% CL For Descriptive Studies only09/03/2010 Dr. Kusum Gaur 16
  11. 11. Finite CorrectionSample Size – Finite Population (where the population is less than 50,000) SSNew SS = _________________ ( 1 + ( SS – 1 ))Pop
  12. 12. How many controls? n k Here n0=No. of cases & 2n0 n n = expected no. of cases• k = 13 / (2*11 – 13) = 13 / 9 = 1.44• kn0 = 1.44*11 ≈ 16 controls (and 11 cases) – Same precision as 13 controls and 13 cases
  13. 13. Sampling Design factors of sample size Variance of Specified SamplingDesign Effect = Variance of Simple Random Sampling (SRS)12/08/2012 Dr. Kusum Gaur 19
  14. 14. Sampling Technique effect on Sample Size Sampling Technique Design Effect Size Multiplier Simple Random Sampling 1 Systemic Random Sampling 1.2 Stratified Random Sampling 0.8 Cluster Random Sampling 2 12/08/2012 Dr. Kusum Gaur 20
  15. 15. Conventionally accepted Researcher’s Estimations Alpha Error 0.05 Power 80% Confidence Limit 95%12/08/2012 Dr. Kusum Gaur 21
  16. 16. Key Concepts: Sample size• Sampling Design - larger sample for Custer• Desired Power – more power for larger sample• Allowable error – smaller error for larger sample• Heterogeneity leads to have larger sample to cover diversities• Nature of Analysis – Complex multivariate needs larger sample 12/08/2012 Dr. Kusum Gaur 22
  17. 17. Steps -Sample Size Estimation • Stage 1- * Base Sample Size Calculation (n) • Stage 2 – Sample Size with Design Effect (d) =n*d • Stage 3- Contingency Addition (e.g. 5%) SS Estimation for study population =(n*d)+5%of n *Use appropriate equation for sample size calculation http://stat.ubc.ca/~rollin/stats/ssize/12/08/2012 Dr. Kusum Gaur 23
  18. 18. E.G. Mean 1= 5, Mean 2 = 15 & SD = 14 inputting values
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  25. 25. Sample Size Tables
  26. 26. SAMPLINGTECHNIQUES
  27. 27. SAMPLING TECHNIQUES• PROBABILITY/RANDOM SAMPLING• NONPROBABILITY SAMPLING12/08/2012 Dr. Kusum Gaur 41
  28. 28. Random sampling Techniques Aim is to give equal chance to every observation unit to be selected for study in sample.(Any Observation unit should not have Zero Probability ) 12/08/2012 Dr. Kusum Gaur 42
  29. 29. * Random Sampling TechniquesSimple Random Technique Systemic Random Technique Stratified Random Technique Multiphase Random Technique Multistage Random Technique Cluster Random Technique 12/08/2012 Dr. Kusum Gaur 43
  30. 30. Simple Random Technique • Lottery Method • Random Table Method12/08/2012 Dr. Kusum Gaur 44
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  32. 32. Steps –Use of Random Table• Stage 1- Give number to each member of population• Stage 2 – Determine total population size (N)• Stage 3- Determine Sample size (S)• Stage 4 – Drop one finger on Random Table with eyes closed• Stage 5 – Drop one finger with eyes closed on direction to be chosen – Up/Down/Rt/Lt• Stage 6- Determine first number within 0 to N• Stage 7- * Determine other numbers till Sample size (S)* Once a number is chosen do not repeat it again 12/08/2012 Dr. Kusum Gaur 46
  33. 33. Steps –Use of Random Table..e.g. N=300, M=50Random no. Selected no. (3 digits from 0-300)494684969914043 04315013 0131260033122 12294169 1698991674169 16932007 007www.evaluation wikiog/index/how_to_use_a_random_number_Table 12/08/2012 Dr. Kusum Gaur 47
  34. 34. Systemic Random Technique The selection of sample follows a systematic interval of selection• Find serial interval (K) = total population/sample size• 1st observation through simple random sampling among 1to K. th• Next observation = (1st +K) Observation• Next observation = (2 nd +K) thObservation• -------------so on till No. of observations = Sample Size12/08/2012 Dr. Kusum Gaur 48
  35. 35. Systemic Random Technique PopulationN=100 (Given) 1 21 41 61 81 2 22 42 62 82S=20 (Estimated) 3 23 43 63 83K=N/S =100/20 =5 4 24 44 64 84 5 25 45 65 851st observation between 1 to 5 6 26 46 66 86 7 27 47 67 87 though SRS e.g. 3 8 28 48 68 88Every 5th observation from 3rd 9 29 49 69 89 10 30 50 70 90 observation will be included in 11 31 51 71 91 sample population 12 32 52 72 92 13 33 53 73 93So, sample population will be – 3rd 14 34 54 74 94 8th 13th 18th 23rd 28th 33rd 38th 15 35 55 75 95 16 36 56 76 96 43rd 48th 53rd 58th 63rd 68th 73rd 17 37 57 77 97 78th 83rd 88th 93rd and 98th 18 38 58 78 98 19 39 59 79 99 observation 20 40 60 80 100 12/08/2012 Dr. Kusum Gaur 49
  36. 36. Stratified Random Technique Sample selection through Simple Random/Systemic Random Technique Sample Strata 1 Sample Strata 2 Sample Strata 312/08/2012 Dr. Kusum Gaur 50
  37. 37. Multiphase Random Technique Specific test Screening Test S/SPopulation Probable cases Cases Suspected cases For study12/08/2012 Dr. Kusum Gaur 51
  38. 38. Multistage Random TechniqueEach stage Simple RT is used village district village village State 1 district Population village Study Of Population Nation village district village State 2 village district village12/08/2012 Dr. Kusum Gaur 52
  39. 39. Cluster Random TechniqueThe unit of random selection is a cluster rather than individual• CI = Total population /30 (in 30 Cluster Technique) Cluster 1 Cluster 27 Cluster 2 Cluster 28 Population Study Of Population Nation Cluster 3 Cluster 29 Cluster 30 Cluster 4 Through Simple RT12/08/2012 Dr. Kusum Gaur 53
  40. 40. Stratified Vs Cluster Technique Stratified Technique Cluster Technique• Homogenous groups are • Comparable groups of made population are made• Randomly select sample (usually 30) from each group • Randomly select sample• To make it more truly from each group representative, take sample population • More chances of error than proportion to size (PPS) simple random• Less chances of error than simple random
  41. 41. Non Probability Sampling • When random samples are not possible • Rare disease • Small population • Special population • Special Condition • Difficult to reach population12/08/2012 Dr. Kusum Gaur 55
  42. 42. Non-probability Samples Convenience  Purposive  Quota  Snow ball study12/08/2012 Dr. Kusum Gaur 56
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  46. 46. Snow ball samplingContact tracingInitial respondent helps in recruiting new populationUseful in network analysis approach12/08/2012 Dr. Kusum Gaur 60
  47. 47. Computer in Statistics12/08/2012 Dr. Kusum Gaur 61
  48. 48. Web sites related to Statistics• http://stattrek.com• http://vassarstat.net• http://www.scribd.com• http://www.statistixl.com• http://statistics calculators.com• http://stat.ubc.ca/~rollin/stats/ssize/• ……………………………………………………………12/08/2012 Dr. Kusum Gaur 62
  49. 49. Computer Softwares in Statistics• Microsoft Excel• SPSS• Epi info• Epi tab• Mini tab• Graph Pad• Primer• Medcal• ……………..12/08/2012 Dr. Kusum Gaur 63
  50. 50. THANKS12/08/2012 Dr. Kusum Gaur 64

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