Chapter 1 usagpan statistics
Transcript of Chapter 1 usagpan statistics
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Statistical Methods for Anesthesia and Intensive Care
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Required Materials/Resources
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Selected Youtube Videos
PrimarySupplement to
facilitate understanding
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Exams
• Chapters 1-4• Chapters 5-9• Chapters 10-13• Comprehensive Final
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Type of Data
Qualitative (Categorical)
Type of Categorization
One categorical variable
Goodness of fit X2
Two categorical variables
Contingency Table X2
Quantitative (Continous)
Type of Question
Relationships
Number of Predictors
One
Measurement
Continuous
Primary Interest
Degree of Relationship
Pearson Correlation
Form of Relationship
Regression
Ranks
Spearman's’ r
Multiple
Multiple Regression
Differences
Number of Groups
Two
Relation between Samples
Independent
Two Sample t Mann-Whitney
Dependent
Related Sample t(paired t tests) Wilcoxon
Multiple
Relation between Samples
Independent
Number of Independent
Variables
One
One Way ANOVAs Kruskal-Wallis
Multiple
Factorial ANOVAs
MultivariateAnalysis
Dependent
Repeated Measures Friedman
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Chapter 1 – Data Types
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Types of Data
• Key Points– Categorical data - nominal and can be counted.– Numerical data may be ordinal, discrete, or
continuous, and are usually measured.– VAS measurements are ordinal data.
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Types of Data
• Qualitative– Data which is descriptive
and characterizes an event and may include an intangible measure of worth or quality.
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Types of Data
• Quantitative– Data which is measured
via a numerical scale.
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Types of Data
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Categorical Data
• Observations are grouped in categories, counted, and sorted accordingly.
• When there are only two categories or choices the data is referred to as binary or dichotomous.
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Categorical Data
• Examples– Gender
• Male• Female
– Type of operation• CABG• Hysterectomy• Cholecystectomy• Appendectomy
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Categorical Data
• Examples– Type of ICU Admission
• Medical• Surgical• Injury• Illness
– Adverse/Untoward Event• NPPE• Positioning nerve injury• Transfusion reaction• PONV
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Categorical Data
• Reporting– Absolute count– Percentages– Rates– Proportions
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Ordinal Data
• Data in which a relative value or ranking can be applied.– Can be viewed as a hybrid between categorical
and numerical data.– The true measure of the data is not tangible but it
does have an essence that is more than just descriptive.
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Ordinal Data• Recording observations
– Typical some type of numerical system is applied.
• Numbers• Roman numerals
– Scoring can also be letters or symbols
• A, B, C, D• +, ++, +++, ++++
• The advantage of a numerical system– Data can undergo nonparametric
statistical analysis.• In a nutshell, using a parametric
statistical analysis on ordinal data.
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Numerical Data
• Quantitative Data– Discrete measurments– Continuous measurements
• Discrete data– Can only be a whole
integer• You cannot have half a
person
• Continuous data– Can take any value
• CBC values• Cardiac Index
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Numerical Data
• There can be further division of Continuous Data.– Interval data– Ratio data
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Numerical Data
• Interval Data– Location of the zero value is arbitrary and not a
true zero point.• Celsius temperature, Dates
• Ratio Data– Simply stated this data has a true zero reference
point.• Kg, m, in., lb, Kelvin temperature
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Numerical Data
• Reporting Numerical Data– Mean– Standard deviation– Median – Range
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A frequent tool used in Anesthesia
• VAS– Can measure, pain,
PONV, anxiety, patient satisfaction.
– When using the 100 mm scale some researchers use erroneously this data as continuous data.
• Is everyone’s pain the same?
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Ranking of Data Types
Ratio Interval
Ordinal
Nominal
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Ranking of Data Types
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Changing Data Scales
• Smoking status can be recorded as smoker/non-smoker (categorical data), heavy smoker/light smoker/ex-smoker/non-smoker (ordinal data), or by the number of cigarettes smoked per day (discrete data).
• MI – ischemia or no ischemia, or the extent of ST segment depression in mm.
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Questions on Chapter 1?
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