128 – Impact of Data Collection Modes and Data Sources
Weighting Mixed Mode Data for the 2015 Residential Energy Consumption Survey (RECS)
Patrick Chen
RTI International
Shaofen Deng
Energy Information Administration
Neeraja Sathe
RTI International
Lanting Dai
RTI International
Rachel Harter
RTI International
Phillip Kott
RTI International
The 2015 Residential Energy Consumption Survey (RECS) was a stratified multistage cluster survey of housing units (HUs). RECS was designed for computer-assisted personal interviewing (CAPI) as the method of data collection. Because of difficulties experienced in the field, CAPI data collection was terminated and replaced with a Web/Mail data collection protocol. Nonrespondents and unfinished cases from CAPI were transferred to Web/Mail, and HUs in reserve replicates of sample were released to Web/Mail. This change imposed a challenge for weighting the combined CAPI and Web/Mail data. In this paper we discuss the weighting class method to adjust for bad addresses and drop points, a latent-variable technique to predict the probability of an address corresponding to an occupied HU, and logistic regression models to estimate the probability of a HU being a primary residence. We used a calibration method to adjust for unit nonresponse and to poststratify the nonresponse-adjusted weights to the estimated number of occupied HUs from the 2015 American Community Survey for specified HU characteristics.