Process of validating a survey
Numerical survey data can be easily handled and analyzed straightforwardly using statistical equations.
On the other hand, ordinal and nominal data need a different way of analyzing survey results.
For instance, you may want to compare the answers of male and female respondents, or young and old participants.
Before inputting the survey data into electronic data files, data coding must be done.
Homogenous subgrouping of the responses makes data analysis faster and easier.
Based on the demographic data gathered from the survey, you may partition the responses into subgroups.
It is a usual practice that ordinal scales (five-point scale, seven-point scale, etc) are converted into their numerical equivalents, as in a five-point scale, where in “strongly agree” is equivalent to “5” whereas “strongly disagree” is equal to “1”.
This table lists specific tools that can be used either to assess a broad range of complex trauma domains or tap into a specific domain in greater detail. Unlike closed-ended questions, open-ended questions are more difficult to code since it needs human expertise to determine if one response is equivalent to another.In this case, several experts are asked to code the responses in order to minimize bias.However, in the case of incomplete questionnaires, you must count the actual number of respondents that were able to answer a particular question.This should be the same for the rest of the questions.
Development and Validation of a Questionnaire to Detect Behavior Change in Multiple Advance Care Planning Behaviors.