Pre-analysis:

  • Research proposal:  Assist in establishing clear research aims and hypotheses, identify appropriate methods for statistical analyses, determine sample size calculation

  • Advise on database design to facilitate importing for data analysis:  data dictionary, variable naming conventions, coding categorical variables and dates, documenting missing data

  • Creating analysis dataset: converting wide to long, long to wide, merging (including using criteria such as “closest” clinic visit, “best” pulmonary function in year, etc.), macros to create new variables

  • Data cleaning: univariable and multivariable summary statistics and figures to identify outliers and data entry errors

Data analysis:

  • Linear regression,hierarchical models, repeated measures analysis, generalized linear models (eg: logistic regression, Poisson regression, etc.)

  • Multivariate data analysis (eg: cluster analysis, factor analysis, etc.)

 

  • Design and evaluation of measurement scales (validity, reliability, item response theory)

 

  • Survival analysis

 

  • Basic statistical methods (ANOVA, t-tests, ChiSquare test, Wilcoxon Rank Sum test, etc.)

Manuscript preparation:

  • Design manuscript quality tables and figures to summarize results

  • Statistical methods and written summary of results

  • Review of results and discussion to ensure accurate interpretation of all results

Biostatistics Consulting:

  • Advise researchers and students on choice of analytic method, help with coding, and assist with interpretation of results

  • 10+ years working with graduate students conducting their own analyses for their thesis and leading biostatistics Q&A sessions for researchers in health care