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1. Contact Kristen Miller (kristen.miller@cuanschutz.edu) to arrange the initial consultation.

2. For services beyond the initial one hour consultation, the investigator will be asked to provide a Children's Â鶹´«Ã½¸ßÇå Cost Center, grant or restricted fund account number. A University department, grant, or gift speed type will also be accepted. 

3. Projects requiring less than 100 hours of work are billed hourly at a subsidized rate* of $75/hour for all investigators. Large projects requiring more than 100 hours of work require %FTE support. We provide up to 40 hours of free support for grant development when biostatistics effort is included in the proposed grant budget.

4. Investigators who are developing grant proposals for future studies must include biostatistics support at an appropriate %FTE when developing their budgets.We generally require at least 10-20% FTE per year, with a 5-10% FTE minimum for small grants. 

5. Please consult with the Core Director when developing your grant budget; in order to effectively plan our resource allocation, unused FTE cannot be carried forward to future years.  The charge for industry-sponsored studies will be at %FTE rates.

In order to help us manage our work requests, we ask you to allow us sufficient time to address your needs. Depending on the nature of the request, a certain minimum turnaround time is required. Please note (below) the following minimum times required:

• Study design (4 weeks)
• Grant application assistance (4 weeks, may overlap with study design)
• Protocol development (4 weeks)
• Data analysis (4 weeks, if no cleaning of data is required e.g. if data are in REDCap)
• Data cleaning (timeline to be determined on a per-case basis)
• Abstract assistance (4 weeks)
• Ongoing collaboration and publication co-authoring – by arrangement.

These are minimum turn-around times, and we may not always be able to adhere to them, particularly if specialized statistical expertise is required.  You can help the statisticians by meeting with them well in advance of your anticipated needs.  We look forward to helping you.

Services provided

• Sample Size Estimation: One of the most important questions in the design of a study is, "How many patients do I need?" We can determine the appropriate sample size for your study so that you will have sufficient statistical power to detect a clinically meaningful effect.
• Randomization Schemes: Are you conducting a randomized study? Our statisticians can produce randomization schemes for your study whether it be randomization for two groups, a stratified randomization, or something more complicated.
• Analysis Plan: The analysis plan is an important component of every study. The types of independent (predictor) variables and dependent (outcome) variables determine the type of statistical analyses that need to be performed, yet the type of analysis determines how the sample size and power are calculated. Our statisticians can design the appropriate analysis plan for your data before the study begins.
• Data Cleaning: Getting the data is half of the battle, and data integrity is paramount. CHBC statisticians can help to identify outliers as well as observations that are biologically impossible. We can also address situations where missing data do not appear to be missing at random.
• Analysis: Once you have your data, our consultants can perform appropriate statistical analyses using a variety of statistical software such as SAS and R. We are experienced in everything from basic statistics to more complex analyses including longitudinal data analysis, multivariate techniques, survival analysis and more. In addition, we can offer guidance in whether and how to adjust for multiple tests.
• Survey/Questionnaire Design: Contrary to popular belief, one cannot and should not write down a couple of questions, call it a questionnaire and then use it to measure a trait for a study. We can instruct you on the process of instrument development and perform statistical analyses for reliability and validity. If you are considering developing an instrument, contact the Child Health Biostatistics Core first.
• Manuscript Preparation: Once the analyses of your data are complete, our statisticians can assist with manuscript preparation by writing the statistical methods, analyses, results, and discussion sections. We can assist you in preparing appropriate tables, graphs, and figures for your manuscript.
• Grant Preparation: Child Health Biostatistics Core statisticians have experience in assisting with grant preparation from stating research hypotheses and aims to identifying endpoints, spelling out the study design, providing the statistical analyses plan, and calculating appropriate sample sizes for the adequate statistical power.
• Protocol Review: Do you need someone to review a completed protocol? We can evaluate your protocol to see if the design, statistical analyses, sample size and power are appropriate for the study. We can also make recommendations to help ensure that your research questions are answered.
• Consulting Statistician for Staff and Professional Meetings: Our statisticians are available to attend staff and research meetings to help your team brainstorm new research projects, evaluate the progress of existing studies, and design new studies.
• Safety Committee: Many Data Safety and Monitoring Boards (DSMB) require a statistician to serve on the board. We have statisticians who can assist with monitoring for safety as well as efficacy or futility.
• Qualitative Analysis and Design of Mixed Methods Research: We have experts in the design and analysis of qualitative research who can help you make sense of the “how and why” behind your data.

• Be a co-author on the publication to acknowledge their intellectual contribution, using their primary appointment affiliation
  
• Analyze data collected for publication and abstracts only after study completion, to maintain study and statistical integrity
• Collaborate with you in structuring the presentation of results and write the statistical methods section of your paper
• Review your publication and any revisions prior to submission
• Assist with revisions, keeping in mind your revision deadlines
  
  

The Child Health Research Biostatistics Core follows the  guidelines concerning authorship.

• First author: The biostatistician plays a major role in project development or hypothesis generation, (when existing data) substantially changes direction of the hypothesis and corresponding analysis, provides a unique contribution, conducts analysis and writes a large portion of your paper.
• Second author: The biostatistician plays a major role in project development, offers statistical expertise needed for your research, or conducts substantial and/or complex analysis of data. This is a typical position for a biostatistician involved in the life cycle of a project or who has unique analytic expertise (e.g., mediation analysis, microbiome or genomics).
• Middle-listed author: The biostatistician does not necessarily collaborate in the design of the study, but conducts data analysis, writes the statistical methods section and assists in interpreting results for conclusion.
• Senior author: The biostatistician provides significant mentoring to the first author, offering guidance for the first author to conduct analysis, or plays a major role in helping the first author design the study. There generally has been substantial one-on-one meeting time as well as additional analysis and paper writing support beyond a typical collaborative role.

New to REDCap? Contact redcap@ucdenver.edu

As you collect data

• Review with statistician and ask for help
• Leave excluded patients in and reason for excluding, with indicator variable to identify as excluded patient
• Include all essential dates for variables and follow ups
• Datasets sent to the statistician just a few days before an abstract deadline will not be analyzed
• Allow for at least 4 weeks for analysis and write-up/presentation preparation AFTER statistician receives the completed and cleaned dataset

Before sending data to a statistician

• Remove PHI
• Review outliers and missing observations (do not remove from the dataset)
• Keep variable names short and meaningful and remove spaces from variable names
• Do not start variable names with a number or special character
• Do not mix character/class and numeric values in the same variable – define as text only if absolutely required
• Be sure categorical variables have the correct number and spelling of categories (i.e. Male, Female. NOT: male, M, female, Female, F)
• Define numeric variables as numeric, not text, and include range checks to prevent invalid data entry
• Remove merged cells and don’t include multiple observations or attributes in a single variable
• Limit text fields to variables not required in the analysis as they can only be used in descriptive reports
• Data on spreadsheets must be free of color/highlighting - use indicator variables to define groups
• Data dictionary must be present, understandable, and include a coding guide for numeric variables