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

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

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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