Pew Research Center 2014 U.S. Religious Landscape Study
SummaryThis dataset is the centerpiece of Pew Research Center's 2014 Religious Landscape Study, a nationally representative telephone survey conducted June 4-Sept. 30, 2014, among a sample of 35,071 U.S. adults. Approximately 60 percent of the interviews were conducted with respondents reached on cellphones (n=21,160) and 40 percent were completed on landlines (n=13,911). A minimum of 300 interviews were conducted in every state and the District of Columbia. Interviewing was conducted in English and Spanish. The survey is estimated to cover 97 percent of the non-institutionalized U.S. adult population; 3 percent of U.S. adults are not reachable by telephone or do not speak English or Spanish well enough to participate in the survey. No adjustments have been made to the data to attempt to account for the small amount of non-coverage.
The size of the national sample is unusually large for a religion survey. There are two main reasons for this. First, the large sample size makes it possible to estimate the religious composition of the U.S. with a high degree of precision. After taking into account the survey's design effect (based on the sample design and survey weights), the margin of error for the results based on the full sample is +/- 0.6 percentage points.
Second, the large sample size makes it possible to describe the characteristics of a wide variety of religious groups, including relatively small groups that cannot be analyzed using data from smaller surveys. With more than 35,000 respondents in total, the Religious Landscape Study includes interviews with roughly 350 in religious groups that account for just 1 percent of the U.S. population, and with 100 or more people in religious groups that are as small as three-tenths of 1 percent of the overall population. For instance, the study includes interviews with 245 Jehovah's Witnesses, a group that accounts for less than 1 percent of the U.S. population and is typically represented by only a few dozen respondents in smaller surveys.
The ARDA has added five additional variables to the original data set to enhance the users' experience on our site.
Data FileCases: 35071
Weight Variable: WEIGHT, WGT_ATL_, WGT_BAL_, WGT_BOS_, WGT_CHI_, WGT_DAL_, WGT_DC_M, WGT_DET_, WGT_HOU_, WGT_LA_M, WGT_MIA_, WGT_MIN_, WGT_NYC_, WGT_PHL_, WGT_PHO_, WGT_PIT_, WGT_PRO, WGT_RIV_, WGT_SEA_, WGT_SF_M, WGT_STL_, WGT_TMP_
All point estimates should be derived from weighted data; point estimates based on unweighted data will not be representative of the U.S. population.
Analysts interested in national-level and state-level data - including those interested in subgroups within the nation or states (e.g., U.S. evangelicals or U.S. Catholics or U.S. women or millennials in California) - should weight the data using the variable WEIGHT. WEIGHT was calculated in two stages. The first stage in the weighting produced base weights that account for several factors, including: 1) the probability of selection of the telephone number, computed separately for each of 102 sampling strata defined by the cross-classification of sample frame (landline and cell phone) and state (including the District of Columbia); 2) the oversampling of "active" numbers in the cell frame; 3) the within-household selection of one respondent per household in the landline frame; and 4) the overlap between the cell and landline frames.
The second stage of the weighting calibrated the base-weighted data to demographic benchmarks for the population covered by the survey. This was performed via iterative proportional fitting (or "raking"). The raking procedure aligned survey respondents to population benchmarks on the following dimensions within each state: Gender by age, gender by education level, education level by age, race/ethnicity, telephone service, and region of state (except for the District of Columbia).
Data CollectionJune 4-Sept. 30, 2014
Original Survey (Instrument)U.S. Religious Landscape Survey
Funded ByPew Charitable Trusts, which received support for the project from the Lilly Endowment Inc.
Collection ProceduresData collection was divided among three research firms - Abt SRBI, Princeton Survey Research Associates International (PSRAI) and Social Science Research Solutions (SSRS). Abt SRBI served as the lead research firm coordinating the data collection, providing the sampling plan and producing the survey weights. Both the landline and cell phone samples were provided by Marketing Systems Group (MSG).
Sampling ProceduresThe national survey employed a dual-frame (cell phone and landline) random-digit dial (RDD) approach to yield a nationally representative sample that included a minimum of 300 completed interviews in every state. This was accomplished by first allocating the total expected number of interviews (approximately 35,000) in states in proportion to their respective share of the national adult population. At this stage, 16 states (including the District of Columbia) were identified in which the proportional allocation would result in fewer than 300 interviews. These 16 states were oversampled to obtain at least 300 interviews in each of them, while the remaining 35 states were undersampled proportionately. The weighting of the data ensures that all states are represented in their proper proportion in the national weighted estimates.
The allocation of sample to the landline or cellphone RDD frame was customized for each state to reflect state-level variation in telephone usage. The amount of sample allocated to cell phone numbers ranged from a low of 35 percent in Rhode Island to a high of 84 percent in Mississippi.
The landline sample was drawn from MSG's 1+ assignment-assisted RDD sampling frame. The cell phone sample was also drawn by MSG, using their Cell-WINS activity flags. The Cell-WINS service appends activity code information to each sampled record, flagging it as active, inactive or "unknown." In the initial cell sample, 59 percent of numbers were flagged as active, 40 percent were flagged as inactive and 1 percent were flagged as unknown. The cell sample was managed such that active and "unknown" numbers were oversampled while inactive numbers were undersampled. Oversampling cell phone numbers flagged as active or "unknown" helps to control survey costs by increasing the amount of interviewer time spent dialing eligible numbers. Retaining some numbers flagged as inactive ensures that the survey's coverage rate was not affected. The weighting of the data corrects for the undersampling of flagged-inactive numbers so that they are represented in their proper proportion in the weighted estimates.
Sampled telephone numbers were called as many as seven times in an effort to obtain a completed interview. Numbers flagged as "callbacks" (i.e., numbers at which a respondent had begun the interview without completing the survey) were called back an additional two times during the final four weeks of the survey period. Refusal conversion was attempted in instances of soft refusals in both the landline and cell phone frames. Calls were staggered over times of day and days of the week to maximize the chance of making contact with potential respondents. Each number received at least one daytime call.
In the landline sample, interviewers asked to speak with the youngest adult at home at the time of the call. In the cellphone sample, interviews were conducted with the person who answered the phone provided the person was age 18 or older. Respondents reached on cell phones were offered a reimbursement of $5 for their cell phone minutes used participating in the survey.
In an effort to maximize the number of interviews with adults who primarily speak Spanish, the study utilized a special protocol in which sampled telephone numbers that service areas with sizable Hispanic populations were dialed by bilingual Spanish- and English-speaking interviewers. Two flags were created in each frame (landline and cell phone) to identify cases with a relatively high probability of requiring Spanish administration. In the landline RDD sample, the first flag identified telephone exchanges with an estimated Hispanic incidence of 65 percent or higher. In the cell frame, the first flag identified numbers that belonged to rate centers (i.e., billing centers) with an estimated Hispanic incidence of 70 percent or higher. These numbers were dialed exclusively by bilingual interviewers capable of conducting the interview in either English or Spanish. There was just one exception to this rule; respondents who completed part of the interview but did not finish the survey and who spoke English were eligible to be called back subsequently by interviewers who spoke only English.
Each frame (landline and cell phone) also included a second Hispanic incidence flag. The second flag in the landline sample identified exchanges with an estimated Hispanic incidence of 60 percent to 64.99 percent. The second flag in the cell frame identified numbers associated with rate centers with an estimated Hispanic incidence of 65 percent to 69.99 percent. In the event that the research firms that conducted the interviewing had bilingual interviewing capacity over and above that needed to dial numbers associated with the first flag, bilingual interviewers were then assigned to numbers identified with the second flag.
Ultimately, 3.8 percent of all interviews were conducted in Spanish, including 4.6 percent in the cell phone sample and 2.5 percent in the landline frame.