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Before-and-after design Have a pretest and posttest but no comparison group,subjects exposed to treatment serve at an earlier time as their own controls Absence of a comparison/control group Validity in experiments Internal validity-causal Generalizability-able to apply the findings to some clearly defined larger population Cross-population generalizability-generalize across subgroups and to oher populations and settings Unrepresentative sample Some characteristics are overrepresented or underrepresented Types of experimental designs Experimental design Quasi-experimental design Nonexperimental design Two types of before-and after designs 1.Time series designs-consisting of many pretests and posttest observations of same group(30 or more) 2. repeated measure panel design-several pretests and post test of same group Two major types of quasiexperimental designs 1. Nonequivalent control group design 2. Before-and-after design Two major types of quasiexperimental designs 1. Nonequivalent control group designs-no random assignment to groups 2. before and after design- has pretest and posttest no comparison group Two functions of Probes 1. They motivate the respondent to elaborate or clarify an answer or to explain reasons 2. they help focus the conversation on the specific topic of the interview True Experiments must have at least 3 things 1. An experimental and control group 2. variation in the independent variable before assessment of change in the dependent variable(treatment) 3. random assignment to two groups Time Series Design Research designs in which pretests and posttests are are available on a number of occassions before and after the introduction of independent variable at least 3 sets of measures before and after O1 O2 O3 X O4 O5 O6 The Principles of Interviewing 1. Respondents need to feel that their interaction with the interviewer will be pleasant and satisfying 2. the respondents need to see the study as being worthwhile 3. barriers to he interview in the respondent’s mind need to be overcome-misperceptions and suspicion of respondent adddressed The Personal Interview Regarded as a face-to-face interpersonal role situation in which an interviewer asks respondents questions to obtains answers related to research hypothesis The Classic Experimental Design Experimental group, control group randomization pretest posttest Telephone survey Or telephone interview A semipersonal method of collecting information,convenient and cost saving method Telephone survey Random digit dialing-draw a random sample of telephone numbers, requires the identification of all working telephone exchanges in the target area.a potential telephone number is created by randomly selecting an exchange and then appending a random number between 0001 and 9999.Additional numbers are created by repeating these two steps.Nonresidential and nonworking numbers are excluded Target population A set of elements larger than or different from the population sampled and to which the researcher would like to generalize study findings. Systematic sampling Select every kth element in a population,where k is determined by dividing the population sixe by the desired sample size. Select a random number between 0 and k and picking that element in the population,systematically pick every kth element Survey Sampling Sampling designed to produce information about particular characteristics of a finite population. Survey research methods Provide ways to describe the variables in populations and to test the relationships among variables in populations. Survey research is popular because of 3 features 1. versatility-cover a range of topics,computer technology has made surveys more versatile 2. efficiency-many variables can be measured without greatly increasing the time or cost 3.generalizabilitylend themselves to probability sampling from large populations. Survey Research Center U of Mich pointers 1. Tell respondent who you are and whom you represent 2. Tell what you are doing to stimulate interest 3. tell how he or she was chosen 4. adapt approach to situation5. try to create relatioship of confidence and understanding-rapport 5. initial instructions should be brief Survey Research Involves the collection of information from a sample of individuals through their response to questions. Stratified samples Done by dividing the population into groups(strata) that are homogeneous on one or more traits,then sampling from each of these groups Stratified Proportionate sample The number of elements selected from each stratum is proportional to that stratum’s representation in the population The same number of sampling units from each stratum or a uniform sampling fraction (n/N) Stratified Disproportionate sample Chosen to yield numbers in a stratum to allow intensive analysis of that particular stratum Variable sampling fractions,total number in each stratum is different,population parameters have to be weighted by the number of each stratum Standard error Allows the researcher to determine the probability that a given sample estimate is close to the actual population value. S.E.=standard error,the distribution of all samples about the mean of the samples is S.E.Calculate standard deviation and estimate the S. E. Simple random sampling Numbering all population elements,then selecting enough random numbers to complete a sample of the desired size.It is simple but inconvenient with large populations Sampling Theory Major objective is to provide accurate estimates of unknown parameters in population from sample statistics Population=parameter sample=statistic Sampling Frame A list of all elements or other units containing the elements in a population Sampling Error -contd The larger the sampling error,the less representative the sample. Sampling Error Any difference between the characteristics of a sample and the characteristics of a population Sampling distribution When an infinite number of independently selected sample values such as the means are placed in a distribution,the distribution is called the sampling distribution Its standard deviation is the standard error Sample generalizability Refers to the ability to generalize from a sample ,or subset of a larger population to that population itself. Sample A subset of a population that is used to study the population as a whole. Subset=sample Research designs are Cross-sectional design– a study in which data are collected at only one point in time or longitudinal design-research in which data are collected at two or more points in time,data can be ordered in time Research Design Is a blueprint for research A plan for collecting,analyzing and interpreting data that allows the investigator to make causal inferences Process for deciding what aspects we’ll observe,of whom,for what purpose Representative sample A sample that “looks” like the population from which it was selected in all respects that are potentially relevant to the study. Random selection procedures Ensure that every sampling unit of the population has an equal and known probability of being included in the sample,the probability is n/N n=sample, N=population Random Selection Each element has an equal chance of selection independent of any other event in the selection process Quota sample Select respondents such that quotas of various types of people are filled in proportion to their prevalence in the population Quasi-experimental design Comparison group comparable to experimental group in critical ways Subjects are not randomly assigned to the groups Quasi-experimental design Subjects are not randomly assigned to to the experimental and control or comparison group Quasi experiments differ from experiments in their lack of Randomization is a defining characteristic of experiments In time series designs the more measurements of the dependent variable you et, the stronger your design Purposive or judgmental sample Select a sample that, in their subjective judgment,is representative of the population Procedures of Control 1. Randomization or random assignment-removes bias from the assignment process by relying on chance-flipping coin or random number table assures that case has an equal probability of being assigned to either group 2. matching- or pairwise matching,for each case in experimental group, another one with identical characteristics is selected for the control group Probing The technique used by the interviewer to stimulate discussion and obtain more information Probability vs. Nonprobability Sampling Probability sample allows estimates to population from sample Nonprobability sample-list of sample population is unavailable-e;g, illegal residents, drug addicts Probability Sample Designs 1. random sample 2. systematic samples 3. stratified samplesproportionate, disproportionate 4. cluster samples 5. multistage samples pretests Measures the dependent variables prior to the experimental intervention,they provide a direct measure of how much the experimental and comparison groups changed over time,tests effects of intervention PPS-probability proportionate to size Type of multistage cluster sample in which clusters are selected,not with equal probabilities(EPSEM) but with probabilities proportionate to their sizes posttest Measurement of the outcome in both groups after the experimental group has received the treatment Post test Only Control Group Design Posttest R R X 01 02 Population-finite or infinite Finite population-contains a countable number of sampling units Infinite population-consists of an endless number of sampling units,an unlimited number of coin tosses Population The entire set of individuals or other entities to which study findings are to be generalized Whole=population Personal interview The questions, their wording and their sequence define the extent to which the interview is structured Omnibus survey A survey that covers a range of topics of interest to different social scientists,example General Social Survey GSS of the National Opinion Research Center at the University of Chicago Nonschedule-structured Interview Focused and structured but the respondents are given much liberty in expressing their definition of a situation that is presented to them.Permits the researcher to obtain details of personal reactions,specific emotions, etc Nonscheduled Interview Least structured form,or nondirective.Noprespecified set of questions is used,nor are the questions asked in a specific order.No schedule is used. With little or no directon from the interiewer, respondents are encouraged to relate their experiences,to reveal opinion and attitude as they see fit. Interviewer has freedom to probe and raise questions Nonprobability Sample Designs 1. Convenience samples 2. purposive or judgmental samples 3. snowball samples 4.quota samples Nonexperimental designs 1. Ex post facto(after the fact) control group design-comparison group selected after treatment occurred 2. one shot case study(cross-sectional Nonequivalent control group Experimental and control/comparison group designated before treatment occurs,not created by random assignment Individual or aggregate matching used Mundane realism Degree to which experiment is superficially similar to everyday situations Internal validity in experiments five threats 1. Selection bias-differential attrition 2. endogeneous change – regression toward mean –extreme scores on dep var become less extreme on post test,testing, maturation-age,experience 3. history effects-effect of external events-disasters 4. contamination – compensatory rivalry(John Henry effect)control group increase effort because denied advantage, demoralization-control group perform worse because left out, Hawthorne effect-treatment group change on dependent variable because participation make feel special Four types of errors in survey research 1. Poor measurement-respondent satisficing when don’t put forth effort 2. nonresponse-perceived benefits of participation have declined 3. inadequate coverage of the population-poor sampling frame 4. sampling error-random sampling due to chance Field Experiment Experimental study conducted in the field, in real-world settings Control over conditions is a big problem External Validation Process of testing the validity of a measure,index ,scale by examining its relation to other presumed indicators of same variable E.g. index of prejudice correlates with other indicators of prejudice Experimental Research Searching for cause and effect The classical experimental design helps us understand the logic of all research designs Experiment is treated as a model against which to evaluate other designs Experimental realism Degree to which experiment absorbs and involves its participants Experimental group Subjects who receive some treatment Experimental design Allows researcher to draw causal inferences and observe whether or not the independent variable caused the dependent variable EPSEM-equal probability of selection method All members of the population have an equal chance of being selected in the sample Is representative of the population from which it is selected Elements The individual members of the sample Demonstrate Causality 3 operations 1. covariation-two or more things vary together(correlation) 2. nonspuriousness-a relation between two variables that cannot be explained by a third variable 3. time order- demonstrate that the assumed cause occurs first or changes prior to the assumed effect Demand Characteristics Cues in an experiment that tells the participant what behavior is expected. In subtle ways the experimenter’s words, tone of voice,gestures may inadvertently demand desired results.To minimize these the experimenter typically standardizes instructions or write or tape record them. Criteria for Causal Explanations 1. Empirical association-variation in one variable is related to variation in another variable 2. appropriate time order –variation in dependent variable occurred after the variation in the independent variable3. nonspuriousness –when a relation between two variables is not due to variation in a third variable Convenience sample Researchers select a sample for study on the basis of what is handy-e.g. teachers using their classes Control group Subjects who do not receive the treatment Confidence level The estimated probability that a population parameter lies within a given confidence interval. 95 percent confident or 99 percent conficent Confidence interval (3) Between – 1Z and +1Z expect to find 68 percent of all sample means,between -1.96Z and +1.96Z find 95 % of all sample means between -2.58Z and +2.58Z expect to find 99 percent of all sample means Confidence interval of -1.96to +1.96 about sample mean(.05),+2.58 and -2.58 is 99 out of 100,or 99 per cent confidence interval (.01) Confidence interval (2) If one knew the mean of all sample means(population mean) and the standard deviation of these sample means 9standard error of the mean) one could compute Z scores and determine the range within which any percentage of the sample means can be found Confidence Interval The range of values within which a population parameter is estimated to lie +-1.96 or +- 2.58 Confidence Interval If the distribution of sample means is normal or approximate normality, we can use the properties of the normal curve to estimate the location of the population mean. Confederate Person posing as a fellow participant in an experiment who is an accomplice of the experimenter Comparison group group of subjects that is exposed to a different treatment from the experimental group Cluster samples Common in large-scale surveys Selecting larger groupings,called clusters,selecting the sampling units from the clusters,clusters selected using simple random or stratified sample Select cluster samples in several stages,such as cities, then blocks,then dwelling units Complete listing of elements in population is not needed Classic research design consists of 3 components 1. comparison-allows to demonstrate covariation 2. manipulation helps in establishing the time order of events,introduce the experimental treatment 3. controlenables to determine that the observed covariation is nonspurious-rule out rival factors Weighting Assigning different weights to cases that were selected into a sample with different probabilities of selection.,each case given weight equal to the inverse of its probability of selection