statistical writing (sven sandin)

Statistical Writing

Sven Sandin,Dpt of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholmhttp://ki.se/en/people/svesan

What will I talk about

The scientific (statistical) method

Manuscript as part of the work flow …. PLANING !

Statistical issuesStatistical significancePowerStatistics section

STROBE

Types of Presentations

Original research papers

- Hypothesis testing

- Descriptive

Meta-analysis

Review

Poster

Conference proceeding

What is important ? Why ?

What is a statistical method ?

What will good procedures achieve

Prevent fraud …..

QA. Increase the value of our own work

Communicating our results with our colleagues

Efficiency and speed

Getting published !

Deduction or Induction

Inductive vs Deductive

Deductive

Top-down

Mathematical logic

A > B …. so A > C

Induction

Bottom-up

Probabilistic

Induction - Statistical inference

Induction

1. Most women are shorter than 185cm2. Maria is a woman3. Maria is most likely shorter than 185

This involves assumptions and earlier knowledge (a) Fact ? assumption ? speculation ? Direction ? Interesting ?(b) Results from the study(c) Conclusion

Where is the weak spot ?

Lawyer ?

Design

What results can the design give us ?

Cause vs association

Generalizability

Confounding

Precision

Types

Cross-sectional

Cohort, case-control

Longitudinal, Cross-over


What is a statistical method ?


Prevent fraud …..




Getting published !



Prevent fraud …..




Getting published !

Most important ?

Repeatability and truth, given this anything is allowed.

State what was done. Pre-specified !

How can we assure that it is possible to repeat ?

........ YOU WILL be asked to re-calculate …..

Structure of the manuscript

Objective ↔ Conclusion

Objective ← Variables & Methods → Results

Don't be afraid of formulating a hypothesis and objectiveIs “Will explore....” good ?Quality grade (strength) ?

Mathematical ...The type phase 3 trial ....Causality

What can the design give us

Need to focus and limit the study.

THIS IS THE SCIENTIFIC (WORK)PROCESS !

Structure of the manuscript

Objective ↔ Conclusion

Objective ← Variables & Methods → Results

Results → Conclusion

Keep focus - Online material

What is a result

Separate what is supported by the data and what is not"A strikingly similar pattern appears for .....""... observed a dramatic increase ...""... it is clear from the data...""... it is borderline significant"

Results arise from the planned process of data collection - else discussion

Discussion section show your expertise judgement

…... sometimes, as a reader, you are not interested in this …..

Is it statistically significant ?

What does it mean ?

Valuable concept - don't trash it !

Be exact and careful“statistical significant” or “significant” ?year or light year ?borderline not statistically significant ??

How much alpha do we have ?

Multiplicity


Four steps1) Set up null and alternative hypothesis. E.g.

H0: m1 = m2, m1 & m2: mean group 1 and 2HA: m1 ≠ m2

2) Define what test to use, e.g. t-test or Wilcoxon rank sum, including significance level

3) Calculate the test statistic and p-value4) Decide: Reject HA or not

Two possible errors in the decision1) Type I (alpha): Conclude difference where there is none. False reject.2) Type II (beta): Fail to conclude a true difference. Fail to reject.

alpha is the risk associated with our final statement


What does it mean ?

Valuable concept - don't trash it !

Be exact and careful“statistical significant” or “significant” ?light year ?borderline not stat sign...

How much alpha do we have ?

Multiplicity

Power

What is it ?

Ethics (but only one part)

Pre-specified

Post-power ?

Precision

Power

The power has a meaning before the data are collected

Calculating power for the observed data is not meaningful

The information sits in the confidence interval

Observed 1-power is the probability that the observed result was false. In other words, there is an effect but sample is to small ...... WRONG!

Power

Hoenig JM, Heisey DM. The Abuse of Power. The American Statistician 2001; 55: 19–24.

Levine M, Ensom MH. Post hoc power analysis: an idea whose time has passed? Pharmacotherapy 2001; 21: 405–9.

Choice of methods/technique

Minimize testing

Test for baseline differences ?

Do you need the assumptions ? ..... check them

Don't dichotomize everything … loss of power .... interpretation.

Missing valuesNot an exclusion criteria … part of methods .... Maximum likelihood and MAR ....Biases ...

The "Statistical methods" section ?

Spell out what you are testingHypothesis ? Method/technique, e.g. logistic regression, Cox regressionWhat assumptions are there ?How have you tested the assumptionsCovariates in the model including categories and how chosenSignificance levelSoftware + version

Any supplementary analysis. What is primary vs supplementary. What was pre-specified and not ?

Missing values

Software

Use standard softwareSASRStataDon't use Excel!

Standard methods

Secure your dataArchive your data, CSV... word ?Save log filesWrite versions in the manuscript

Other softwareLibreoffice, www.libreoffice.orgZotero, www.zotero.org

Manuscript as part of the work flow

When do the manuscript writing start ?

Study plan is crucial !

The results are published independent on the outcome !! Plan for this!

(Statistical) Analysis plan

Statistical Analysis Plan

What is it ?Communication

(Statistical) Analysis plan

Objective

Clarifies roles - list of authors

Methods and need for competences

Pre-specify: Guide later analyses

Write the introduction and methods before the data are available

What is a bad paper/study

?

Summary

What do we want to achieve ?

Probabilistic vs certain

Possible to repeat

Work flow

statistical writing (sven sandin)

Education