The Maternal and Child Health Bureau (MCHB), the Centers for Disease Control and Prevention (CDC), and CityMatCH will again offer a Training Course in Statistics and Epidemiological Methods as part of their ongoing effort to enhance the analytic capacity of state and local health agencies. The training course is an intensive program that combines lectures, discussion, hands-on exercises, and opportunities for individualized technical assistance. Two webinars prior to the training will set the stage for the onsite course and several post-course webinars will serve to build upon and extend the in-person training.
Content will include background and methods for the following, as they relate to the MCH planning cycle:
Needs Assessment and Priority Setting
Perinatal Periods of Risk (PPOR)
Multivariable Analysis and Regression Modeling
Effective Data Presentation and Translation
Who Should Apply
This national program is aimed primarily at professionals in state and local health agencies who have significant responsibility for collecting, processing, analyzing, and reporting maternal and child health data. This year, the course is geared to individuals with basic to intermediate skills in statistics and epidemiologic methods, preferably in Maternal and Child Health or a related field. Note: Only applicants who work domestically and regularly analyze data rather than manage programs, will be considered.
If you have intermediate to advanced skills and regularly apply regression analysis, we welcome you to apply to next year's course, and to review course materials from the 2018 intermediate to advanced course.
If you are a program manager, please see the training links below for data users.
Training will begin mid-day June 24, 2019 and conclude mid-day June 28, 2019 in Charleston, SC.
Hotel room lodging at the Hyatt Place Charleston Historic DIstrict is included in the training.
A limited number of scholarships for airfare are available.
Applications will be competitively reviewed, and acceptance notifications issued in April.