DE-MYSTIFYINGDE-MYSTIFYING
BIOSTATISTICSBIOSTATISTICS
Minimum Set of Items Needed for
Protocol Preparation Meeting with
GC...
Sequence & Cycle of
Research
1. Choosing the research question
2. Developing the protocol
3. Pretesting and revising the p...
Why Plan a Research
Project?
To Avoid Unanticipated Problems!
 Improper assignment of subjects to
treatments
 Unexpected...
The Exercise and Value of
Mental Planning
– with colleagues familiar with the research
topic and with related research
– w...
Ten Steps for Designing a
Study
1. Develop a good idea
2. Decide on objectives and establish priorities
3. Determine the v...
Minimum Set of Items to
Bring to First Meeting with
Statistician
• General research question(s)
• The design of the study
...
Developing Research
Question(s)
• State the Aim(s) of the research
project
• Prioritize (rank) the Aims
• Categorize the A...
Refining the Research Aims
into Quantitative Expression
Once the research aims have been
written they need to be refined s...
Choosing the Study
Design
• Observational Study
(Observing subjects under existing conditions)
– Descriptive study
– Analy...
Choosing the Study
Subjects
1. Conceptualize the target population
The large group of people with a specified set of
chara...
Defining Response
Variables
• Categorical Variables
– Nominal (gender, ethnicity, blood type)
– Ordinal (degree of pain, s...
Variables of Interest
Variable
Name
Variable
Type
Upper/
Lower
Limits
Example Notes
Gender Categorical LL=0
UL=1
0=Female
...
Variable Time Line
Variable Visit #1 Visit #2 Visit #3 Visit #4
Gender X
Weight X X X X
Number
Cigarettes
X X X X
Tumor
Gr...
Sample Size Techniques for
Descriptive Studies
Estimates for Proportions
The sample size needed depends on
two things:
– T...
Width of Exact 95%
Confidence Intervals for
Sample Sizes 25-500 and
Proportion Values 0.5, 0.75
(0.25), 1.00 (0.0)
Sample
...
Sample Size Techniques for
Descriptive Studies
Estimates for Means
The sample size needed depends on two
things:
– To what...
Sample Size & Precision for
95% Confidence Intervals
about Mean
Sample
Precision Size
0.715 10
0.468 20
0.373 30
0.320 40
...
Sample Size & Precision for
95% Confidence Intervals
about Mean
Precision vs N with C.C.=0.95
S=1.000 C.I. Mean
Precision
...
Power/Sample Size
Considerations for
Experimental/Analytical
Studies
Tests of Means
• The statistical test must be specifi...
Sample Size/Power for
Independent t-test for Equal Size
Groups and Equal Variances
Assumed
Difference in
Means*
N for Each...
Sample Size/Power for Paired
(One Sample) t-test
Difference in
Means*
Number
Pairs
90% Power
Number
Pairs
80% Power
Popula...
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DE-MYSTIFYING BIOSTATISTICS

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DE-MYSTIFYING BIOSTATISTICS

  1. 1. DE-MYSTIFYINGDE-MYSTIFYING BIOSTATISTICSBIOSTATISTICS Minimum Set of Items Needed for Protocol Preparation Meeting with GCRC Biostatisticians Christie E. Burgin, PhD, GCRC Biostatistician Donald E. Parker, PhD, GCRC Biostatistician
  2. 2. Sequence & Cycle of Research 1. Choosing the research question 2. Developing the protocol 3. Pretesting and revising the protocol 4. Carrying out the study 1. Analyzing the findings 2. Drawing and disseminating the conclusions
  3. 3. Why Plan a Research Project? To Avoid Unanticipated Problems!  Improper assignment of subjects to treatments  Unexpected large variability among subjects  Unrealistic schedule for study completion  Inadequate or no data management
  4. 4. The Exercise and Value of Mental Planning – with colleagues familiar with the research topic and with related research – with research facilitators – with a statistical consultant – with current/recent literature – with friends – with family members – with self
  5. 5. Ten Steps for Designing a Study 1. Develop a good idea 2. Decide on objectives and establish priorities 3. Determine the variables required 4. Select and describe the study population 5. Refine objectives into quantitative addressable hypotheses or estimates 6. Anticipate error and bias 7. Develop the study design 8. Estimate the sample size needed 9. Write a research proposal for review 10. Plan the data collection
  6. 6. Minimum Set of Items to Bring to First Meeting with Statistician • General research question(s) • The design of the study • Who the subjects will be • What information (response variables) you wish to obtain from each subject • Information for sample size/power calculations
  7. 7. Developing Research Question(s) • State the Aim(s) of the research project • Prioritize (rank) the Aims • Categorize the Aims – Primary Aims – Secondary Aims • Obtain Feedback on Decisions – from colleagues – from self
  8. 8. Refining the Research Aims into Quantitative Expression Once the research aims have been written they need to be refined so that Aims may be addressed in a quantitative manner.
  9. 9. Choosing the Study Design • Observational Study (Observing subjects under existing conditions) – Descriptive study – Analytical study • Experimental Study (Random allocation of subjects)
  10. 10. Choosing the Study Subjects 1. Conceptualize the target population The large group of people with a specified set of characteristics to which the results of the study will be generalized 2. Identify an accessible subset of the population Sample that will represent the target population 3. Design an approach to sampling the population Probability sampling Nonprobability sampling 4. Design approaches to recruiting Design contact mechanisms for acquiring a sample of subjects that is large enough to meet the study needs, and that has acceptable levels of technical error and nonresponse bias
  11. 11. Defining Response Variables • Categorical Variables – Nominal (gender, ethnicity, blood type) – Ordinal (degree of pain, severity of accident, tumor grade) • Measurement Variables – Discrete ( number of cigarettes smoked/day, number of children in family) – Continuous (weight, blood pressure, cholesterol, fasting blood sugar)
  12. 12. Variables of Interest Variable Name Variable Type Upper/ Lower Limits Example Notes Gender Categorical LL=0 UL=1 0=Female 1=Male Weight Measure 150 lbs Number Cigarettes Measure 12 per day Tumor Grade Categorical LL=1 UL=4 Level 1
  13. 13. Variable Time Line Variable Visit #1 Visit #2 Visit #3 Visit #4 Gender X Weight X X X X Number Cigarettes X X X X Tumor Grade X
  14. 14. Sample Size Techniques for Descriptive Studies Estimates for Proportions The sample size needed depends on two things: – To what precision you wish to estimate the proportion – Where in the interval from zero to one the proportion resides
  15. 15. Width of Exact 95% Confidence Intervals for Sample Sizes 25-500 and Proportion Values 0.5, 0.75 (0.25), 1.00 (0.0) Sample Size Value of Proportion 1.00 (0.0) 0.75 (0.25) 0.5 500 0.00735 0.07775 0.08943 400 0.00918 0.08714 0.10018 300 0.01222 0.10098 0.11600 200 0.01828 0.12436 0.14268 100 0.03622 0.17777 0.20336 50 0.07112 0.25266 0.28945 25 0.13719 0.36189 0.40926
  16. 16. Sample Size Techniques for Descriptive Studies Estimates for Means The sample size needed depends on two things: – To what precision you wish to estimate the mean – The standard deviation of the observations from which mean was obtained
  17. 17. Sample Size & Precision for 95% Confidence Intervals about Mean Sample Precision Size 0.715 10 0.468 20 0.373 30 0.320 40 0.284 50 0.258 60 0.238 70 0.223 80 0.209 90 0.198 100
  18. 18. Sample Size & Precision for 95% Confidence Intervals about Mean Precision vs N with C.C.=0.95 S=1.000 C.I. Mean Precision N 0.1 0.3 0.5 0.7 0.9 0 20 40 60 80 100
  19. 19. Power/Sample Size Considerations for Experimental/Analytical Studies Tests of Means • The statistical test must be specified • Researcher must specify the size differences he/she wants to detect
  20. 20. Sample Size/Power for Independent t-test for Equal Size Groups and Equal Variances Assumed Difference in Means* N for Each Group 90% Power N for Each Group 80% Power Population Between Means 0.25 337 252 10% 0.50 86 64 19% 0.75 39 29 27% 1.00 23 17 34% 1.25 15 12 39% 1.50 11 9 43% 1.75 8 7 46% 2.00 7 6 48% 2.25 6 5 49% *Standard Units-to convert to study units multiply standard units by estimate of within group standard deviation
  21. 21. Sample Size/Power for Paired (One Sample) t-test Difference in Means* Number Pairs 90% Power Number Pairs 80% Power Population Between Means 0.25 171 128 10% 0.50 44 34 19% 0.75 21 16 27% 1.00 13 10 34% 1.25 9 8 39% 1.50 7 6 43% 1.75 6 5 46% 2.00 5 5 48% 2.25 5 4 49% *Standard Units-to convert to study units multiply standard units by estimate of standard deviation of differences

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