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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