Descriptive Methods Ch. 6 and 7 Purpose of Descriptive Research Purely descriptive research describes the characteristics or behaviors of a given population in a systematic and accurate fashion. Correlational research is often considered descriptive research as well Describing the associations or relationships between 2 or more variables Types of Descriptive Research Survey is type of descriptive research that may use either questionnaires or interviews to collect data. Cross-sectional survey design: a single group or respondents (a cross-section of the population) is surveyed. Successive independent sample survey design: two or more samples of respondents answer that same questions at different points in time. Validity depends on samples being comparable 1
Surveys Longitudinal or panel survey design: a single group of respondents is questioned more than once. Problem is drop-out the sample no longer the same as before. Makes it difficult to know whether changes in data are due to real changes in behavior or due to changes in the sample who provided the data. Internet Surveys http://psych.hanover.edu/research/exponn et.html Advantages: Inexpensive don t require printing, postage, or team of interviewers Don t have to enter data program does it May be able to recruit subjects it would be difficult to find in person (late night, distant) Disadvantages: Little control over selecting sample: pulls certain types of respondents Can t be sure of the nature of the sample Types of Descriptive Research Demographic research describes patterns of basic life events and experiences, e.g. marriage, birth, divorce, death, employment, immigration Epidemiological research used to study the occurrence of disease in different groups of people 2
Sampling Sampling is the process by which a researcher selects a sample of participants for a study from the population of interest. Representative sample: a sample from which we can draw accurate, unbiased estimates of the characteristics of the population Probability Samples Sampling error differences between the sample and the population Sampling error causes the results obtained from the sample to differ from what would have found if entire population had been studied. Researchers can estimate how much their results are affected by sampling error. Error of estimation (margin of error) degree to which the data from the sample are expected to deviate from the population as a whole. Probability Samples Error of estimation is a function of 3 things: Sample size Population size Variance of the data The larger a probability sample, the more similar to the population the sample tends to be. Can t always obtain a large sample opt for an economic sample one that provides most accuracy for least cost and effort 3
Probability Samples Size of population the smaller the population the smaller the error of estimation The greater the variability in the data, the more difficult it is to estimate accurately the population values. The larger the variance, the less representative the mean is of the scores as a whole. Larger variance = need larger sample Schedule Quiz Ch 6 today No Quiz on Ch 7 NO CLASS ON MARCH 8th since so many already planning to be gone Quiz on Ch 8 when we return from Spring Break Monday, March 20th Research Hypothesis with operationalizations (e.g. how are you going to measure) of variables - due on March 20th Probability Samples Error of estimation is only meaningful when we have a probability sample. A probability sample is a sample for which the researcher knows the probability that any individual in the population is included in the sample. Usually choose a design in which all individuals in the population have an equal chance of being selected for the sample. 4
Probability Samples 3 basic ways of drawing a probability sample: Simple random sampling Stratified random sampling Cluster sampling Simple random sampling: every possible sample of the desired size has the same chance of being selected. Need a sampling frame a list of the population from which the sample will be drawn. Probability Samples Random numbers table or generator: commonly used method for random selection # the cases in your population Take 200 #s the subjects corresponding to those #s are chosen for the study 4856 3494 2427 1789 4242 3528 1111 3742 2772 2170 27 1210 2820 1532 2446 1979 990 3811 3923 1627 2229 735 1156 1219 4441 2579 1689 4503 3496 3112 2229 3668 2947 4824 339 1331 4071 2396 2053 1082 Probability Samples Stratified Random Sampling rather than selecting cases directly- first you divide the population into two or more strata Stratum subset of population that shares a particular characteristic Stratification ensures that you have adequate #s of subjects from each strata. Proportionate sampling method cases are sampled from each strata in proportion to their prevalence in the population. 5
Probability Samples Cluster sampling Break target population in to groups or clusters, first randomly select clusters, then select participants randomly from within each cluster. Cluster sampling often involves a multistage sampling process begin by sampling large clusters, then sample smaller clusters from within large clusters, then even smaller clusters, then participants. Problems with Probability Samples The problem of nonresponse: failure to obtain response from individuals that researchers select for their sample Possible solutions: Try to decrease nonresponse rate - follow-up on mailings with phone calls, include return postage and envelopes (e.g. make it as easy as possible for subject to respond) Determine whether respondents and nonrespondents differ systematically Problems with Probability Samples Misgeneralization: if researcher generalizes results to a population that differs from the one from which the sample was drawn 6
Non-probability Samples Don t know the probability that a particular case will be chosen for the sample, thus can t calculate the error of estimation. When research is designed to test hypotheses regarding how variables related to behavior, then non-probability sample is appropriate. 3 basic types of non-probability samples Convenience samples Quota samples Purposive samples Non-probability Samples Convenience sample: Researchers use subjects who are readily available. Quota sample: Convenience sample in which the researcher takes steps to ensure that certain kinds of participants are obtained in particular proportions. Purposive sample: Researchers use their judgment to decide which participants to include in the study, trying to choose those who are more typical of population. Before Doing Survey Research What is your hypothesis? Surveys best answer descriptive hypotheses describing a phenomena or population Let hypotheses guide creation of survey Otherwise may end up with a lot of useless information Helps to plan analyses first make sure you are getting the data that you need Run through different possible outcomes to see if different outcomes have different implications (e.g. opposite of your hypothesis would you have the data to explain difference) 7
Different Survey Instruments How to choose depends on: Cost Response rate Honesty of respondents Standardization Different Survey Instruments Self-administered questionnaires: filled out by participants without assistance from investigator (often investigator absent) Advantages: can be easily administered to a lot of people, allows anonymity Drawbacks: low return rate may lead to biased sample, can t correct problems with respondent s understanding of the questionnaire, may not be able to control conditions in which respondent answers questions (e.g. people helping, distractions) Different Survey Instruments Investigator-Administered Questionnaires: filled out in presence of investigator Advantages: Can be done in a variety of locations Investigator can clarify questions for respondent Investigator presence encourages responding Disadvantages: Reduces sense of anonymity Increased cost of investigator presence 8
Different Survey Instruments Interviews Advantages: Interaction with the participant can clarify questions, follow-up on unclear or interesting responses Personal interaction increases response rate Disadvantages More time consuming and costly Interviewer bias Greater demand for respondent to impress interviewer social desirability bias Different Survey Instruments Telephone Interviews Advantages: Can be monitored/recorded to check standardization Because can t see respondent nonverbal cues can t contribute to interviewer bias or social desirability bias Also greater anonymity over phone Fewer problems with sampling bias use random digit dialing Convenient, less time consuming Different Survey Methods Telephone interviews Disadvantages: Still possibility of sampling bias (not all have phones, or listed #s) Nonresponse is problem Have to ask simple, short questions Only know what respondent tells you can t see for yourself (similar to problems of internet surveys) 9
Format of Questions Fixed alternative versus open-ended Dichotomous versus continuous Fixed Alternative Questions: respondents choose between 2 or more responses True/false, multiple choice, rating scales Open-Ended Questions: participants free to respond in their own words Advantages: don t put words in participants mouths, find out beliefs/opinions behind their response Disadvantages: greater demands for participants, difficult to score due to wide variety Format of Questions Dichotomous items: participants only have 2 answer choices (e.g. yes or no) Advantages: easier to decide, easier to interpret so tends to be reliable Disadvantages: frustrating to reduce view point to yes or no answer, may lose power by artificially dichotomizing a variable Format of Questions Likert-type items: respondents choose from a range, usually 5 point scale ranging from strongly disagree to strongly agree Yields more information, can use more powerful statistical tests Can sum to get a total score 10