Training

This tutorial will demonstrate how to use a SAS macro to help with pooling multiple years of CHIS data files.

This presentation reviews several commonly used statistical disclosure limitation (SDL) techniques that are used to protect sensitive government data. The presenter demonstrates these techniques in practice by presenting case studies and shares useful resources for further guidance on available techniques used to protect its data.

CHIS hosted a data user training webinar for legislators and media on how to use CHIS' free online data tools to get data on a wide range of health topics. This webinar featured AskCHIS™, AskCHIS Neighborhood Edition™, and COVID-19 data dashboards, as well as preliminary monthly estimates from new COVID-19 questions in CHIS 2020.

CHIS hosted a data user training webinar for legislators and media on how to use CHIS' free online data tools to get data on a wide range of health topics. This webinar featured AskCHIS™, AskCHIS Neighborhood Edition™, and COVID-19 data dashboards, as well as preliminary monthly estimates from new COVID-19 questions in CHIS 2020.

The California Health Interview Survey (CHIS) hosted a training webinar to demonstrate how to use CHIS' free online data tools -- AskCHIS, AskCHIS Neighborhood Edition, and COVID-19 Data Dashboards -- to get data on a wide range of health topics across many sociodemographic factors.

The California Health Interview Survey (CHIS) hosted a training webinar to demonstrate how to use CHIS' free online data tools -- AskCHIS, AskCHIS Neighborhood Edition, and COVID-19 Data Dashboards -- to get data on a wide range of health topics across many sociodemographic factors.

This seminar discusses trends in capturing multiracial identity and the implications for researchers. As more surveys allow respondents to identify with the multiple races that reflect their identity, data managers are working on strategies for developing the best methods to most accurately reflect the population.

This seminar helps the audience understand the capacity for machine learning, addresses the barriers to data disaggregation, and discusses what to consider when using technology as a solution to improve your data disaggregation.