Chapter 1 usagpan statistics
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Chapter 1 usagpan statistics






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Chapter 1 usagpan statistics Chapter 1 usagpan statistics Presentation Transcript

  • Statistical Methods forAnesthesia and Intensive Care1
  • Required Materials/Resources2Selected Youtube VideosPrimarySupplement tofacilitateunderstanding
  • Exams• Chapters 1-4• Chapters 5-9• Chapters 10-13• Comprehensive Final3
  • Type of DataQualitative(Categorical)Type ofCategorizationOnecategoricalvariableGoodness of fitX2TwocategoricalvariablesContingencyTable X2Quantitative(Continous)Type ofQuestionRelationshipsNumber ofPredictorsOneMeasurementContinuousPrimaryInterestDegree ofRelationshipPearsonCorrelationForm ofRelationshipRegressionRanksSpearmans’ rMultipleMultipleRegressionDifferencesNumber ofGroupsTwoRelationbetweenSamplesIndependentTwo Sample t Mann-WhitneyDependentRelated Sample t(paired t tests)WilcoxonMultipleRelationbetweenSamplesIndependentNumber ofIndependentVariablesOneOne WayANOVAsKruskal-WallisMultipleFactorialANOVAsMultivariateAnalysisDependentRepeatedMeasuresFriedman
  • Chapter 1 – Data Types5
  • Types of Data• Key Points– Categorical data - nominal and can be counted.– Numerical data may be ordinal, discrete, orcontinuous, and are usually measured.– VAS measurements are ordinal data.6
  • Types of Data• Qualitative– Data which is descriptiveand characterizes anevent and may includean intangible measure ofworth or quality.7
  • Types of Data• Quantitative– Data which is measuredvia a numerical scale.8
  • Types of Data9
  • Categorical Data• Observations are grouped in categories,counted, and sorted accordingly.• When there are only two categories or choicesthe data is referred to as binary ordichotomous.10
  • Categorical Data• Examples– Gender• Male• Female– Type of operation• CABG• Hysterectomy• Cholecystectomy• Appendectomy11
  • Categorical Data• Examples– Type of ICU Admission• Medical• Surgical• Injury• Illness– Adverse/Untoward Event• NPPE• Positioning nerve injury• Transfusion reaction• PONV12
  • Categorical Data• Reporting– Absolute count– Percentages– Rates– Proportions13
  • Ordinal Data• Data in which a relative value or ranking canbe applied.– Can be viewed as a hybrid between categoricaland numerical data.– The true measure of the data is not tangible but itdoes have an essence that is more than justdescriptive.14
  • Ordinal Data• Recording observations– Typical some type of numericalsystem is applied.• Numbers• Roman numerals– Scoring can also be letters orsymbols• A, B, C, D• +, ++, +++, ++++• The advantage of a numericalsystem– Data can undergononparametric statisticalanalysis.• In a nutshell, using a parametricstatistical analysis on ordinaldata.15
  • Numerical Data• Quantitative Data– Discrete measurments– Continuous measurements• Discrete data– Can only be a wholeinteger• You cannot have half aperson• Continuous data– Can take any value• CBC values• Cardiac Index16
  • Numerical Data• There can be further division of ContinuousData.– Interval data– Ratio data17
  • Numerical Data• Interval Data– Location of the zero value is arbitrary and not atrue zero point.• Celsius temperature, Dates• Ratio Data– Simply stated this data has a true zero referencepoint.• Kg, m, in., lb, Kelvin temperature18
  • Numerical Data• Reporting Numerical Data– Mean– Standard deviation– Median– Range19
  • A frequent tool used in Anesthesia• VAS– Can measure, pain,PONV, anxiety, patientsatisfaction.– When using the 100 mmscale some researchersuse erroneously thisdata as continuous data.• Is everyone’s pain thesame?20
  • Ranking of Data TypesRatio Interval Ordinal Nominal21
  • Ranking of Data Types22
  • Changing Data Scales• Smoking status can be recorded assmoker/non-smoker (categorical data), heavysmoker/light smoker/ex-smoker/non-smoker(ordinal data), or by the number of cigarettessmoked per day (discrete data).• MI – ischemia or no ischemia, or the extent ofST segment depression in mm.23
  • Questions on Chapter 1?24