UQUMRC KAMC Biostatistics for your Research Proposal 2012

Statistics for Your
Research Proposal
SohailBajammal, MBChB, MSc, FRCS(C), PhD(c)
Assistant Professor of Orthopaedics, Umm Al-Qura University
Director of CME & Research Administration, King Abdullah Medical City Makkah

bajammal

What Statistics do you need to know
for your proposal?
• Types of Variables

• Types of Statistics

• How to Choose a Statistical Test?

• Hypothesis Testing & Sample Size

Patho Physiology of Research
Research Study Plan Actual Study
Question Design Implement

Target Intended
Actual subjects
Population Sample

Errors Errors
Actual
Phenomena Intended
measurements
of interest variables

Truth in the Truth in the Findings in
Universe Infer Study Infer the Study
External Validity Internal Validity
From Hulley et al. Designing Clinical Research. LWW

Variables
• Anything whose value can vary

• Dependent (response) variable: outcome

• Independent (explanatory) variables: predictors

• Confounding variable: associated with the
independent variable and a cause of the dependent
variable
– coffee drinking (independent), MI (dependent)
– cigarette smoking (confounder),

Types of
Variables

Categorical Quantitative
(Continuous or
“Qualitative” Discrete)

Nominal Ordinal Interval Ratio

Nationality Stage I, II, III Temperature Pulse
Gender & IV cancer (0 is not zero) (0 is dead)

Implications of Types of Variable
• Details of data collection forms
– Age:
• ……. Years Ratio
• <20yr, 21-30yr, 31-40yr, >40 Ordinal

• Choice of statistical analysis test

• Coding in the statistical software: 1,2 for nominal
– Does not make sense to have a mean for nominal

• BIAS if you didn’t consider confounders

When deciding on your variables
• Think of patient-oriented outcomes, instead of
disease-oriented outcomes

• Studying the effect of new drugs on
arrhythmia, which is better as outcome?
– Number of arrhythmia
– Frequency of palpitation/Quality of Life

Statistics deals with
• Collection
• Organization
• Analysis
Data
• Interpretation

Types of Statistics
Statistics

Descriptive Inferential
Statistics Statistics

Measures
Measures What Confidence
of Central Interval
of Spread test?
Tendency

Inter-
Standard
Mean Median Mode quartile
Deviation
Range

Descriptive Statistics

• Numerical
• Tabulated
• Graphs

Measures of Central Tendency
• Mean: average

• Mode: most frequent count

• Median: the value separating the top and
bottom of data (organized highest to lowest)

Measures of Central Tendency

Best measure of
Type of Variable
central tendency

Nominal Mode

Ordinal Median

Interval/ratio
Mean
(not skewed)
Interval/ratio
Median
(skewed)

Difficult Exam Scores!!

Laerd.com

Measures of Spread (Variability)
• Standard Deviation
• Percentile
• Range &Interquartile Range

Standard Deviation
Variability of values
around the mean

Variance

Standard
Deviation

Courtesy of Prof. Hassan Baaqeel

Differences in Standard Deviation
Bell-shaped curve

0.08

0.07 Mean = 70 SD = 5

0.06

0.05
Density

0.04
Mean = 70 SD = 10
0.03

0.02

0.01

0.00

40 50 60 70 80 90 100
Grades

Normal Distribution
MEAN

68 % of
observations 1 SD

2 SD
95 % of observations

99.7 % of observations 3D
-3 -2 -1 0 1 2 3

STANDARD DEVIATIONS
Courtesy of Prof. Hassan Baaqeel

Inferential Statistics

• Allow for making predictions, estimations or
inferences about what has not been observed
(the whole population) based on what has
(the sample)

• Every time we use inferential statistics we risk
being wrong by chance
– We need a range of values to be confident
(Confidence Interval)

Hypothesis Testing
• When we compare two groups, we are testing a
hypothesis

• Null Hypothesis (HO):
– there is no difference between the groups
– (e.g., no difference in mortality)

• Alternate Hypothesis (HA):
– there is a difference

• We choose a statistical test to do the hypothesis testing

Chi-square
Mann-Whitney

Statistical Tests
t-test
Kruskal-Wallis
ANOVA

How to Choose a Statistical Test?
• Your Question:
– Difference between groups or correlation/prediction

• Variables:
– Types: nominal, ordinal, interval or ratio
– Distribution: normal or skewed

• Groups:
– Number: two or more
– Relationship: related or un-related

Probably the simplest/coolest

City College Coventry

Choice of Statistical Tests
Parametric Non-Parametric
Tests Tests
Interval/Ratio 1. Ordinal
Goal (normal 2. Interval/Ratio Nominal
distribution) (skewed)

Comparison of 2
Unpairedt-test Mann-Whitney U
unrelated groups
Chi-square Test
Comparison of >2
ANOVA Kruskal-Wallis H
unrelated

Comparison of 2
Paired t-test Wilcoxon
related groups
Binomial Sign Test
Comparison of >2 Repeated measures
Friedman
related groups ANOVA

Correlation Pearson’s Spearman’s rho Chi-square Test

All the inferential tests are “estimation”
• We need a CONFIDENCE INTERVAL

• It is a range of values that if the estimate
occurs in this range, we will be confident that
it is not due to chance

• How much error are we willing to accept ?
– α< 0.05

Paul Mathews, Design of Experiments with MINITAB, 2005, ASQ Press

Hypothesis Testing (α&β errors)
Null Hypothesis: No association between predictor & outcome
Truth in the Population
Results in the
Study Sample Association Between No Association Between
Predictor & Outcome Predictor & Outcome

Reject null
Correct Type I error (α)
hypothesis

Fail to reject null
Type II error (β) Correct
hypothesis

Type I & II Errors
• Type I (α) Error: usually 1-5%
– Rejecting the null hypothesis when it is actually true
– Stating that there is a difference, while in truth there is no
difference

• Type II (β) Error: usually 10-20%
– Failing to reject null hypothesis when it is actually false
– Stating that there is no difference, while in truth there is a
difference
– Statistical Power of the Study = 1-β

What do you need to know
in statistics for your proposal?
• Types of Variables
• Types of Statistics
• How to Choose a Statistical Test?
• Sample Size

bajammal

UQUMRC KAMC Biostatistics for your Research Proposal 2012

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