Survey research

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Survey research books

Survey research is often used to assess thoughts, opinions, and feelings.[1] Survey research can be specific and limited, or it can have more global, widespread goals. Today, survey research is used by a variety of different groups. Psychologists and sociologists often use survey research to analyze behavior, while it is also used to meet the more pragmatic needs of the media, such as, in evaluating political candidates, public health officials, professional organizations, and advertising and marketing directors. A survey consists of a predetermined set of questions that is given to a sample.[1] With a representative sample, that is, one that is representative of the larger population of interest, one can describe the attitudes of the population from which the sample was drawn. Further, one can compare the attitudes of different populations as well as look for changes in attitudes over time. A good sample selection is key as it allows one to generalize the findings from the sample to the population, which is the whole purpose of survey research. "


The sample is chosen from the sampling frame, which consists of a list of all members of the population of interest.[1] The goal of survey research is not to describe the sample, but the larger population. This generalizing ability is dependent on the representativeness of the sample, as stated above. Each member of the population is termed an element. There are frequent difficulties one encounters while choosing a representative sample. One common error that results is selection bias. Selection bias results when the procedures used to select a sample result in over representation or under representation of some significant aspect of the population. For instance, if the population of interest consists of 75% females, and 25% males, and the sample consists of 40% females and 60% males, females are under represented while males are overrepresented. In order to minimize selection biases, stratified random sampling is often used. This is when the population is divided into sub-populations called strata, and random samples are drawn from each of the strata, or elements are drawn for the sample on a proportional basis. So survey is pretty important in sociology which sociologists often use this technique.

The quality of the sample can often tilt the quality of results. A representative and generalizable sample mitigate both the sampling and non-sampling error. Several sources provide a useful understanding of concepts in this area. They include research by Hansen et al. (1953)[2] and Salant et al. (1994).[3]

Correlation and causality[edit]

When two variables are related, or correlated, one can make predictions for these two variables.[1] However, it is important to note that this does not mean causality. At this point, it is not possible to determine a causal relationship between the two variables; correlation does not imply causality. However, correlation evidence is significant because it can help identify potential causes of behavior. Path analysis is a statistical technique that can be used with correlational data. This involves the identification of mediator and moderator variables. A mediator variable is used to explain the correlation between two variables. A moderator variable affects the direction or strength of the correlation between two variables. A spurious relationship is a relationship in which the relation between two variables can be explained by a third variable.

Research Designs[edit]

There are several different designs, or overall structures, that can be used in survey research. The three general types are cross-sectional, successive independent samples, and longitudinal studies[1]

Cross-Sectional Studies[edit]

In cross-sectional studies, a sample (or samples) is drawn from the relevant population and studied once[1] A cross-sectional study describes characteristics of that population at one time, but cannot give any insight as to the causes of population characteristics because it is a predictive, correlational design.

Successive Independent Samples Studies[edit]

A successive independent samples design draws multiple random samples from a population at one or more times[1] This design can study changes within a population, but not changes within individuals because the same individuals are not surveyed more than once. Such studies cannot, therefore, identify the causes of change over time necessarily. For successive independent samples designs to be effective, the samples must be drawn from the same population, and must be equally representative of it. If the samples are not comparable, the changes between samples may be due to demographic characteristics rather than time. In addition, the questions must be asked in the same way so that responses can be compared directly.

Longitudinal Studies[edit]

Longitudinal studies take measure of the same random sample at multiple time points[1] Unlike with a successive independent samples design, this design measures the differences in individual participants’ responses over time. This means that a researcher can potentially assess the reasons for response changes by assessing the differences in respondents’ experiences. Longitudinal studies are the easiest way to assess the effect of a naturally-occurring event, such as divorce that cannot be tested experimentally. However, longitudinal studies are both expensive and difficult to do. It’s harder to find a sample that will commit to a months- or years-long study than a 15-minute interview, and participants frequently leave the study before the final assessment. This attrition of participants is not random, so samples can become less representative with successive assessments. To account for this, a researcher can compare the respondents who left the survey to those that did not, to see if they are statistically different populations. Respondents may also try to be self-consistent in spite of changes to survey answers.


Questionnaires are the most commonly used tool in survey research. However, the results of a particular survey are worthless if the questionnaire is written inadequately[1] Questionnaires should produce valid and reliable demographic variable measures and should yield valid and reliable individual disparities that self-report scales generate[1]

Questionnaires as tools[edit]

A variable category that is often measured in survey research are demographic variables, which are used to depict the characteristics of the people surveyed in the sample[1] Demographic variables include such measures as ethnicity, socioeconomic status, race, and age[1] Surveys often assess the preferences and attitudes of individuals, and many employ self-report scales to measure people’s opinions and judgements about different items presented on a scale[1] Self-report scales are also used to examine the disparities among people on scale items[1] These self-report scales, which are usually presented in questionnaire form, are one of the most used instruments in psychology, and thus it is important that the measures be constructed carefully, while also being reliable and valid.[1]

Reliability and validity of self-report measures[edit]

Reliable measures of self-report are defined by their consistency[1] Thus, a reliable self-report measure produces consistent results every time it is executed[1] A test’s reliability can be measured a few ways[1] First, one can calculate a test-retest reliability[1] A test-retest reliability entails conducting the same questionnaire to a large sample at two different times[1] For the questionnaire to be considered reliable, people in the sample do not have to score identically on each test, but rather their position in the score distribution should be similar for both the test and the retest[1] Self-report measures will generally be more reliable when they have many items measuring a construct[1] Furthermore, measurements will be more reliable when the factor being measured has greater variability among the individuals in the sample that are being tested[1] Finally, there will be greater reliability when instructions for the completion of the questionnaire are clear and when there are limited distractions in the testing environment[1] Contrastingly, a questionnaire is valid if what it measures is what it had originally planned to measure[1] Construct validity of a measure is the degree to which it measures the theoretical construct that it was originally supposed to measure[1]

Composing a questionnaire[edit]

Six steps can be employed to construct a questionnaire that will produce reliable and valid results[1] First, one must decide what kind of information should be collected[1] Second, one must decide how to conduct the questionnaire[1] Thirdly, one must construct a first draft of the questionnaire[1] Fourth, the questionnaire should be revised[1] Next, the questionnaire should be pretested[1] Finally, the questionnaire should be edited and the procedures for its use should be specified[1]

Guidelines for the effective wording of questions[edit]

The way that a question is phrased can have a large impact on how a research participant will answer the question[1] Thus, survey researchers must be conscious of their wording when writing survey questions[1] It is important for researchers to keep in mind that different individuals, cultures, and subcultures can interpret certain words and phrases differently from one another[1] There are two different types of questions that survey researchers use when writing a questionnaire: free response questions and closed questions[1] Free response questions are open-ended, whereas closed questions are usually multiple choice[1] Free response questions are beneficial because they allow the responder greater flexibility, but they are also very difficult to record and score, requiring extensive coding[1] Contrastingly, closed questions can be scored and coded much easier, but they diminish expressivity and spontaneity of the responder[1] In general, the vocabulary of the questions should be very simple and direct, and most should be less than twenty words[1] Each question should be edited for "readability" and should avoid leading or loaded questions[1] Finally, if multiple items are being used to measure one construct, the wording of some of the items should be worded in the opposite direction to evade response bias[1]

Order of questions[edit]

Survey researchers should carefully construct the order of questions in a questionnaire[1] For questionnaires that are self-administered, the most interesting questions should be at the beginning of the questionnaire to catch the respondent’s attention, while demographic questions should be near the end[1] Contrastingly, if a survey is being administered over the telephone or in person, demographic questions should be administered at the beginning of the interview to boost the respondent’s confidence[1]

Thinking critically about survey research[edit]

Reported behavior versus actual behavior: The value of collected data completely depends upon how truthful respondents are in their answers on questionnaires[1] In general, survey researchers accept respondents’ answers as true. Survey researchers avoid reactive measurement by examining the accuracy of verbal reports, and directly observing respondents’ behavior in comparison with their verbal reports to determine what behaviors they really engage in or what attitudes they really uphold[1] Studies examining the association between self reports (attitudes, intentions) and actual behavior show that the link between them—though positive—is not always strong—thus caution is needed when extrapolating self-reports to actual behaviors,[4][5][6]


  1. ^ a b c d e f g h i j k l m n o p q r s t u v w x y z aa ab ac ad ae af ag ah ai aj ak al am an ao ap aq ar as at au av Shaughnessy, J.; Zechmeister, E.; Jeanne, Z. (2011). Research methods in psychology (9th ed.). New York, NY: McGraw Hill. pp. 161–175. 
  2. ^ Hansen, Morris H., William N. Hurwitz, and William G. Madow. "Sample Survey Methods and Theory." (1953).
  3. ^ Salant, Priscilla, I. Dillman, and A. Don. How to conduct your own survey. No. 300.723 S3.. 1994.
  4. ^ Morwitz, Vicki G., and David Schmittlein. "Using segmentation to improve sales forecasts based on purchase intent: Which" intenders" actually buy?." Journal of Marketing Research (1992): 391-405.
  5. ^ Chandon, Pierre, Vicki G. Morwitz, and Werner J. Reinartz. "Do intentions really predict behavior? Self-generated validity effects in survey research." Journal of Marketing 69.2 (2005): 1-14.
  6. ^ Ajzen, Icek, and Martin Fisbbein. "Factors influencing intentions and the intention-behavior relation." Human Relations 27.1 (1974): 1-15.