The Health Care Priorities and Experiences of California Residents
Appendix A: Survey Methodology
The Kaiser Family Foundation/California Health Care Foundation California Health Policy Survey was conducted by telephone November 12 – December 27, 2018 among a random representative sample of 1,404 adults age 18 and older living in the state of California (note: persons without a telephone could not be included in the random selection process). Interviews were administered in English and Spanish, combining random samples of both landline (476) and cellular telephones (928, including 668 who had no landline telephone). Sampling, data collection, weighting and tabulation were managed by SSRS in close collaboration with Kaiser Family Foundation and California Health Care Foundation researchers. The California Health Care Foundation paid for the costs of the survey fieldwork, and Kaiser Family Foundation contributed the time of its research staff. Both partners worked together to design the survey and analyze the results.
The sampling and screening procedures were designed to increase the number of Black and Asian-American respondents and low-income respondents, including those who have health insurance through Medi-Cal or who are uninsured. This oversample allowed for sufficient numbers of respondents in these subgroups to report their results separately; weighting adjustments were made to adjust their proportions to represent their actual shares of the population in overall results (see weighting description below). The sample included 463 respondents who were reached by calling back respondents in California who had previously completed an interview on either the SSRS Omnibus poll or the Kaiser Health Tracking Polls and indicated they fit one of the oversample criteria (Black, Asian, or low-income respondents, including low-income respondents with Medi-Cal or who are uninsured, and are living in California). It also included 46 respondents with prepaid (or pay-as-you-go) cell phone numbers in California, a group that is disproportionately lower-income.
The dual frame cellular and landline phone sample was generated by Marketing Systems Group (MSG) using random digit dial (RDD) procedures. The RDD frames were stratified by income-level in order to reach more low-income respondents. To address the fact that some qualifying respondents could be reached only by their cell-phone but had an out-of-state phone number, the sample was augmented with a sample of phone numbers outside of California associated with a billing address that indicated in-state residence (n=89). Survey Sampling International (SSI) generated these numbers randomly using Smart Cell sample. All respondents were screened to verify that they resided in California. For the landline sample, respondents were selected by asking for the youngest adult male or female currently at home based on a random rotation. If no one of that gender was available, interviewers asked to speak with the youngest adult of the opposite gender. For the cell phone sample, interviews were conducted with the qualifying adult who answered the phone.
A multi-stage weighting design was applied to ensure an accurate representation of the California adult population. The first stage of weighting involved corrections for sample design, including accounting for the components, the likelihood of non-response for the re-contacted sample, and an adjustment to account for the fact that respondents with both a landline and cell phone have a higher probability of selection. In the second weighting stage, demographic adjustments were applied, at first, to the RDD and Smart Cell sample to account for systematic non-response along known population parameters. Population parameters included gender, age, race, Hispanic ethnicity (broken down by nativity), educational attainment, phone status (cell phone only or reachable by landline), and state region. Demographic parameters were based on estimates from the U.S. Census Bureau’s March 2017 American Community Survey (ACS), and telephone use was based on data for California from the 2016 National Health Interview Survey. Based on this second stage of weighting, estimates were derived for self-reported income as a percentage of the federal poverty level (less than 200%, 200% or higher) by insurance status (Medi-Cal, uninsured, all else) in the California population. The last stage of weighting included all respondents and used poverty level by insurance status, based on the previous stage’s outcomes, as an additional weighting parameter.
The margin of sampling error including the design effect for the full sample is plus or minus 3 percentage points. For results based on subgroups, the margin of sampling error may be higher. Sample sizes and margins of sampling error for subgroups are available by request. Note that sampling error is only one of many potential sources of error in this or any other public opinion poll. Kaiser Family Foundation public opinion and survey research is a charter member of the Transparency Initiative of the American Association for Public Opinion Research.
California regions analyzed in this report are defined as follows:
- Los Angeles County
- South Coast: San Diego and Orange Counties
- Inland Empire: Riverside and San Bernadino Counties
- San Joaquin Valley: San Joaquin, Stanislaus, Merced, Madera, Fresno, Kings, Tulare, and Kern Counties
- Sacramento/North Valley: Shasta, Tehama, Glenn, Butte, Colusa, Yuba, Placer, Sutter, Yolo, El Dorado, and Sacramento Counties
- San Francisco Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Sonoma, and Solano Counties