In coming months—through public appearances, news features, media releases, and scholarly studies—the HLS team will provide additional detail from the survey responses and continue to highlight insights and provoke further research into how Indiana residents, scientists, businesses, and public officials can work together to build resilient communities. Scientists predict that over the next 50 years our state’s average temperature will increase by 5°F to 6°F. Additionally, we will see more frequent and intense precipitation events, leading to more flooding, especially in the spring. Some areas of the state could see up to a six-fold increase in the number of extremely hot days (over 95°F) in the next 30 years (Widhalm et al. 2018). You can find complete survey results—and tailor them to address the questions that most interest you and your neighbors—on our interactive website, https://eri.iu.edu/tools-and-resources/hoosier-life-survey-opinion-map.html.
Appendix 1: Methods
The survey from which data for this report were drawn was sent out to 10,000 Hoosiers between August and December 2019. The survey focused on gathering a broad range of information related to Indiana residents’ views of their community, environmental changes and risk, climate change beliefs, the household- and community-level actions they were taking or supported being pursued, and their personal values. Surveys were sent to Indiana households using a spatially stratified sampling approach. To ensure adequate coverage of people across the entire state and for later geographically specific analysis, our team developed eight in-state regions, defined by clusters of counties. Each of Indiana’s 92 counties was included in a region. From each region, 1,250 home addresses were drawn at random from the United States Postal Service’s list (for a total of 10,000), which was purchased from a private address-based sampling vendor.
In mailing surveys to these households, a modified Dillman approach was used with a total of five mailing-waves (Dillman, Smyth, & Christian, 2014). In an initial wave of mailings, households received a cover letter informing them about the survey, noting the confidentially of their responses and asking them to fill out the survey online. A link to the online survey and user ID number were provided in the cover letter. Roughly two weeks later, a reminder postcard was sent to all sampled individuals who had yet to respond. After approximately another two-week period, respondents who had yet to fill out the survey online were sent a paper booklet version of the survey and another cover letter requesting their participation. A final mailing wave, containing another booklet and cover letter, was sent to all remaining non-participants after another two-week period. Both the initial contact for the web-based survey and the mail-based version contained $2 pre-incentive payments. Upon completing the survey, respondents could request a $20 Amazon or Walmart gift card. In total, our response rate was just over 27 percent. Case-wise deletion analysis was used to address missing data in this report, resulting in 1,500 cases being examined. Patterns of missing data were explored, as were relationships between missing responses and key demographics. No consistent patterns emerged, nor were strong relationships identified. In terms of differences between the full and complete samples, average age of respondents was the only significantly different demographic variable (average of 51 versus 50 years old, respectively). In consequence, this data may slightly over-represent younger respondents. Future HLS reports and data products may use data imputation methods depending on analysis type and the variables of interest. There is also the potential for some bias introduced bias the question design.
To ensure accurate population estimates for this analysis, survey weights were used. Weighting incorporates: (1) a base weight adjustment for unequal probabilities of selection due to disproportionate stratified sampling by region and due to the number of adults in the household, (2) a differential nonresponse adjustment to correct for unequal response rates by stratum/region, and (3) a calibration adjustment to 2018 American Community Survey estimates on gender, age, education, race, and Hispanic origin in the Indiana adult population. Weights were trimmed and scaled to the unweighted number of respondents.
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