Response rates are vitally important to survey-based research studies because the level of error and the studies’ findings are ultimately linked to the response rates. The Council of American Survey Research Organization’s (CASRO) definition of a research survey response rate is “the ratio of the number of interviews to the number of eligible units in the sample” (CASRO 1982). It is important to calculate response rates accurately because they are one measure of the potential bias in the research data, with a high response rate indicating a lower potential bias. Alternatively, when low response rates occur, a non-response bias may exist, whereby there is a systematic difference between those who do and do not respond to a survey measurement instrument. If and when non-response bias is present (e.g., non-respondents differ significantly from respondents) then results can be false or misleading, and results cannot be generalized to the entire population being studied.