Download Type 1

Easy (and not so easy) questions
to ask about adolescent health
data
J. Dennis Fortenberry MD MS
Indiana University School of Medicine
Four types of questions about
health data
• About data users
• About data production
• About data quality
• About data inferences
Questions about users
Questions about the users
• Who are the end-users
• What are the data skills of the end-users
• What are the conditions of use
Questions about data
production
Questions about data production
• Why were the data collected
• Who collected the data
• How were the data collected
• How were the data processed
Questions about data production
• Who is represented by the data
• Who is left out – and why
• Are there issues of privacy and
confidentiality
Questions about data quality
Questions about data quality
• Missing data
• Incorrect data
• Coded data
• Out of range data
• Accuracy
Precision and Accuracy
Accurate &
Precise
True Value
True Value
Precise
only
True Value
Accurate
only
Neither Accurate
nor Precise
True Value
Questions about data
inferences
What type of data is available
• Nominal
• Ordinal
• Interval
• Ratio
Measurement Scales
• Nominal
• Ordinal
A nominal scale produces
categorical variables
• Interval
• Ratio
Interval and Ratio scales produce
continuous variables
Examples of Measurement Scales
Nominal
Temperature (0F)
Ordinal
Blood Pressure
Interval
Tanner Stage
Ratio
Gender
What type of descriptive statistics
are needed
• Mean
• Median
• Shape of distribution
• Variation – standard deviation
• Proportion
Mean
-1 SD
+1 SD
-2 SD
+ 2 SD
-1.96 SD
+1.96 SD
For a normal curve, a traditional alpha
is nearly two standard deviation
units from the mean
Standard Deviation
• A measure of variability within a sample
• Positive square root of variance
• Area between - 1SD and +1 SD
represents 68% of area under the curve
• Between -2 SD and +2 SD is 95.4%
Confidence Intervals
• Range of values containing true mean
with a given level of certainty
• 95% CI commonly used
• 95% CI = mean  1.96 SE
The Null Hypothesis
H0: A does not differ from B
H1: A is different than B
Where A and B are two variables
of interest
Types of Error in Statistical Testing
• Type 1: Rejection of a ‘true’ null
hypothesis
• Type 2: Acceptance of a ‘false’ null
hypothesis
One-Tail versus Two-Tails
• One-Tailed tests are used to assess a
directional hypothesis
• One-tailed tests have greater power
• One-tailed tests can be used when
there is solid theoretical or empirical
basis
Elements of Statistical Power
• The statistical test
• Level of Alpha
• 1-Tailed / 2-Tailed
• Sample Size
• The difference to be detected
What type of inferential statistics
are appropriate
• Correlation
• Chi square
• t test
• Risk ratio and Odds ratio
What is a Risk Ratio
Risk
Factor
Disease Status
Total
Present
Absent
Present
a
b
a+b
Absent
c
d
c+d
Total
a+c
b+d
a+b+
c+d
What is an Odds Ratio
Risk
Factor
Disease Status
Total
Present
Absent
Present
a
b
a+b
Absent
c
d
c+d
Total
a+c
b+d
a+b+
c+d
Who do the data represent and
Can the data be applied to other
groups
• Representativeness
• Generalizability
Questions?