This presentation is the property of its rightful owner.
1 / 36

# Statistical analyses in the real world PowerPoint PPT Presentation

Statistical analyses in the real world. Paul Williams Lawrence Berkeley National Laboratory. Statistical significance. Theory: The probably of observing something by chance Practice: The accepted threshold P<0.05 is publishable P>0.05 is not publishable

Statistical analyses in the real world

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

## Statistical analyses in the real world

Paul Williams

Lawrence Berkeley National Laboratory

### Statistical significance

• Theory: The probably of observing something by chance

• Practice: The accepted threshold

• P<0.05 is publishable

• P>0.05 is not publishable

• The promise to produce P<0.05 is a primary consideration for NIH funding

### Choice of an appropriate statistical test

• Familiarity to the reader, reviewer, granting agency

• Succinctness, in consideration of journal space, simplicity in presenting results

• Statistical tests promise the world, which we can then promised to funding agencies, journals, etc.

### Relationship of average BMI to weekly distance walked in women

kg/m2

Williams PT.Med Sci Sports Exerc. 2005 371893-901.

### Relationship of percentiles of the BMI distribution to weekly distance walked in women

kg/m2

Williams PT.Med Sci Sports Exerc. 2005 371893-901.

### Regression slope by percentile

Slope (kg/m2 per km/wk)

Williams PT.Med Sci Sports Exerc. 2005 371893-901.

### Decline in BMI per km/wk run or walked

Slope (∆BMI per 1km difference in

weekly distance)

Williams PT.Med Sci Sports Exerc. 2005 371893-901.

### Q-Q plot of female runners’ and walkers’ BMI distribution

Walkers’ BMI distribution

### Estimated change in BMI per one km/wk difference in running distance

Slope (∆BMI per 1km difference in

weekly distance)

### Published applications:

“… the effects of physical activity, alcohol, and weight

reduction on HDL-C levels may be, to a large extent,

dependent on the initial level with the greatest

improvement achieved in subjects with high HDL

and the least improvement in those having low

HDL-C levels.”

Williams PT.The relationships of vigorous exercise,

alcohol, and adiposity to low and high high-density

lipoprotein-cholesterol levels.Metabolism.

2004 Jun;53(6):700-9.

### Published applications:

“We speculate that the reported greater increases in

triglycerides per unit of adiposity in whites than blacks,

in men than women, and in low-density lipoprotein

(LDL) pattern B than A are all consistent with the

relationships we observe.”

Williams PT. Relationship of adiposity to the population

distribution of plasma triglyceride concentrations in

vigorously active men and women. Atherosclerosis.

2004 Jun;174(2):363-71.

### Published applications:

“We speculate that the reported greater increases in

triglycerides per unit of adiposity in whites than blacks,

in men than women, and in low-density lipoprotein

(LDL) pattern B than A are all consistent with the

relationships we observe.”

Williams PT. Relationship of adiposity to the population

distribution of plasma triglyceride concentrations in

vigorously active men and women. Atherosclerosis.

2004 Jun;174(2):363-71.

### Published applications:

“These results are consistent with the hypothesis that

running promotes the greatest weight loss specifically

in those individuals who have the most to gain from

losing weight.”

Williams PT. Vigorous exercise and the population

distribution of body weight.Int J Obes Relat Metab

Disord. 2004 Jan;28 (1):120-8

### After assigning significance, the second most important contribution of statistics to research scientist is adjustment

• For example, walkers may be leaner than nonwalkers but is it because they eat better.

• Statistical adjustment is usually a sufficient argument for journals, funding agencies, etc.

Triglycerides (mmol/L)

% reduction

Williams PT.Metabolism

. 2004;53:700-9.

## 3. Analysis of change data

DBMI=a +bDdistance

Cross-sectional

relationship

BMI

Distance

### Translating change data into a relationship

Doesn’t correspond

To:

DBMI=a +

bDdistance

gDdistance2

Cross-sectional

relationship

BMI

The amount of change depends upon the starting and ending distance

### Exposure model relating DBMI to change in running distance

Estimated DBMI due to a “dj-cj” km/wk change

in running distance

Williams PT, Wood PD. Int J Obes (Lond). 2006 30:543-51

## 4. Measurement error

### Original interpretation of ACLS

Blair SN, et al. JAMA. 1995;273:1093-8.

### Variables measured with error

Williams PT. Med Sci Sports Exerc. 2003;35:736-40.

### Our interpretation of ACLS

Fitness measured

Fitness measured

Williams PT. Med Sci Sports Exerc. 2003;35:736-40.

### Simulation versus reported results

Williams PT. Med Sci Sports Exerc. 2003;35:736-40.