DE-MYSTIFYING DE-MYSTIFYING BIOSTATISTICSBIOSTATISTICS

Minimum Set of Items Needed for Protocol Preparation Meeting with

GCRC Biostatisticians

Christie E. Burgin, PhD, GCRC BiostatisticianDonald E. Parker, PhD, GCRC Biostatistician

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

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

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

Ten Steps for Designing a Study

1. Develop a good idea2. Decide on objectives and establish priorities3. Determine the variables required4. Select and describe the study population5. Refine objectives into quantitative addressable

hypotheses or estimates6. Anticipate error and bias7. Develop the study design8. Estimate the sample size needed9. Write a research proposal for review10. Plan the data collection

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

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

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.

Choosing the Study Design

• Observational Study (Observing subjects under existing conditions)

– Descriptive study– Analytical study

• Experimental Study (Random allocation of subjects)

Choosing the Study Subjects

1. Conceptualize the target populationThe 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 populationSample that will represent the target population

3. Design an approach to sampling the populationProbability samplingNonprobability sampling

4. Design approaches to recruitingDesign 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

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)

Variables of Interest

Variable Name

Variable Type

Upper/Lower Limits

Example Notes

Gender Categorical LL=0UL=1

0=Female1=Male

Weight Measure 150 lbs

Number Cigarettes

Measure 12 per day

Tumor Grade

Categorical LL=1UL=4

Level 1

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

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

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

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

Sample Size & Precision for 95% Confidence Intervals

about Mean

SamplePrecision Size0.715 100.468 200.373 300.320 400.284 500.258 600.238 700.223 800.209 900.198 100

Sample Size & Precision for 95% Confidence Intervals

about Mean

Precision vs N with C.C.=0.95S=1.000 C.I. Mean

Pre

cis

ion

N

0.10.30.50.70.9

0 20 40 60 80 100

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

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

Sample Size/Power for Paired (One Sample) t-test

Difference in Means*

Number Pairs90% 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