discussion board questions/ experimental design activity
General Issues in Research Design
Chapter 3
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Introduction
- Science is an enterprise dedicated to finding out
- No matter what we want to find out there are many ways to go about it
- All aspects of research design are interrelated
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Foundations of Social Science
- The two pillars of science logic/reasoning and observation
- This means that –
A scientific understanding of the world must make sense and
Must agree with what we observe
- These pillars relate to the three key aspects of scientific research:
Theory
Data collection
Data analysis
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Foundations of social science
- Scientific theory deals with the logical aspect of science
- Data collection deals with observational aspect
- Data analysis look for patterns in what is observed eg. whether there is a link between 2 variables or whether certain group are more likely to show certain attributes
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Theory, Not philosophy or belief
- Social Scientific theory has to do with what is, not what should be
- A theory is a systematic explanation for the observed facts and laws that relate to a particular aspect of life eg juvenile delinquency (strain theory)
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Theory
Theory: a set of concepts/ideas and the proposed relationship among these concepts;
a structure that is intended to represent or models something about the world
Used to guide research and develop a hypothesis
A researcher can use “routine activity theory” to generate a hypothesis about patterns of burglary
Hypothesis is an expectation about the nature of things derived from a theory
Hypothesis testing: involves finding out if observations are consistent with the hypothesis
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Regularities and Exceptions
Goal of theory is to find patterns of regularity in social life. We assume that life is regular.
Norms and rules in society create regularity eg
teenagers commit more crimes than adults; students go to school, judges receive higher salaries than social workers
Exceptions do not negate regularities – patterns still exist
Social regularities represent probabilistic patterns: patterns need not be reflected in 100% of observations
Probabilistic prediction: women are less likely to murder anybody, but when they do, their victims are usually males
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Aggregates, Not Individuals
Social scientists study social patterns, or aggregates/entire sum, not individual behavior
Although researchers study motivations that affect individuals, aggregate are the subject of SS research
EX. A researcher studying whether White inmates tend to be assigned to more desirable jobs than non-white inmates wld be interested in patterns of job assignment
Social scientific theories care about why aggregated patterns of behavior are regular even when participating individuals change over time
The focus is on patterns and variables
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Variables and Attributes
Social scientists study variables & the attributes that compose them
A Variable is an element or number that increases or decreases over time, or changes in different situations.
Attributes - characteristics that describe some object/person eg. old fashioned, employed, married
Variables - logical groupings of attributes
Male and female are the attributes of the variable gender
Gender is the variable composed of logical grouping of those two attributes. see
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Variables and Relationships
Causation – an attribute of one variable is expected to cause, predispose, or encourage an attribute of another variable eg private attorney caused a person to be sentenced to probation
Independent variable: “cause”, “influencer” – can cause corresponding changes in other variables
Dependent variable: “effect”, “depends” – can take different values in response to an independent variables; eg. sentence depends (DV) on the type of attorney (IV)
Eg. Type of defense attorney (IV) effects prison or probation (DV)
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Idiographic and Nomothetic Explanations – the way we explain things
- Idiographic explanations: seek a full and detailed understanding of a single case or situation
- Eg. different explanations of why you have done poorly in an exam. Case Study
- Nomothetic explanations: are partial explanations that explain a class of situations or events rather than a single one.
Eg. you do better in an exam if you study alone than if u study in a group
You get more speeding tickets on weekends than on week days
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Example of Idiographic Explanations
Clifford R. Shaw developed idiographic explanations to understand the lives of juvenile delinquents.
These case studies, offered researchers a comprehensive view of the effect that variables such as family factors, peer influences, and community circumstances have on the engagement in juvenile delinquency.
Data collection involved interviews with the youths and their parents, analyzing diaries kept by the youths, and reviewing juveniles medical, school, and arrest records.
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Inductive and Deductive Reasoning
Deductive reasoning: moves from the general to the specific
From a logically or theoretically-expected pattern to observations that test the presence of the pattern.
From general statements towards observations. See pg. 59
Inductive reasoning: moves from the specific to the general
From a set of observations to general statement or the discovery of a pattern among them. See pg. 59
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Qualitative and Quantitative Data
All observations are qualitative at the outset
Qualitative = non-numerical; greater detail, greater richness of meaning
e.g., What constitutes “maturity” or “being rich”?
Quantitative = numerical; carries a focusing of attention and specification of meaning
Makes it easier to summarize data and allows for statistical analysis
e.g., a person’s age
Both are useful and legitimate – choose based on topic or combine aspects of both
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Causation in Social Sciences
- One of the goals of social scientific research is to explain why things are the way they are
- We do that by specifying the causes for the way things are
- Some things are caused by other things
- Cause is probabilistic eg. certain factors make delinquency more or less likely
Victims of Childhood abuse are more likely to report alcohol abuse as adults;, or upbringing, peer influence
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Criteria for Causation
What criteria must be satisfied before we can infer that something causes something else
2 Criteria for assessing an idiographic explanation (Maxwell 2013):
How credible and believable it is ie. logic, make sense
Whether alternative explanations (rival hypothesis”) were seriously considered
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Criteria for causation
3 Criteria for assessing an Nomothetic explanation (Shadish, Cook & Campbell, 2002):
1. In a causal relationship between two variables the cause must precede the effect in time
Which comes first: drug abuse or crime
2. The two variables must be empirically correlated with each other – they must occur together
3. The observed empirical correlation between the two variables cannot be explained by the influence of some other variable
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Validity and Causal Inference
When we are concerned with whether we are correct in inferring that a cause produced an effect, we are concerned with validity – whether it is true and valid
When we say something is valid, we make judgment about the extent to which relevant evidence supports that interference as being true or correct
Validity threats: reasons we might be incorrect in stating that some cause produced some effect
- Validity threats - a way that you might be wrong
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Does drug use cause crime?
- Understanding causal statements about drug use and crime requires:
Carefully specifying 2 key concepts –drug use and crime
And considering the different ways these concepts might be related
- The 3 criteria for inferring cause –
- Time order – which comes first, drug use or crime?
Chaiken (1982) found that 12% of their adult subjects committed crimes after using drugs for at least 2 years
Whereas 15% committed predatory crimes 2 or + years b/4 using drugs
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3 criteria for inferring cause cont.
- Empirical relationship –
Studies have found that some drug users commit crimes and some criminals use drugs
Bernett (2008) found that drug users are three times more likely to commit crime than non users
This establishes statistical relationship
- Eliminating alternative explanations
What about the possible influence of other factors, things that might be related to both drug use and crime
Chaiken concludes that Both drug use and crime participation are weakly related
Presence of other factors like strain suggest that the relationship is not directly causal
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Units of Analysis 1
Unit of analysis also known as units of observation: what or who is studied
Individuals - (individual people may be partly defined as police, victims, defendants, inmates, gang members, burglars)
Groups - multiple persons with same characteristics - (gangs, police beats, patrol districts, households, city blocks, cities, counties)
Organizations - formal organizations with established leaders and rules - (prisons, police departments, courtrooms, drug treatment facilities, businesses, agencies)
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Unit of Analysis 2
Social artifacts –products of social behavior or social interactions among people –
Egs. stories about crime in newspapers,
video posts on the Internet showing actual crimes,
photographs of crime scenes,
incident reports, police/citizen interactions
E.g. A researcher could analyze whether videos are actual recordings of crime in progress or reports of crime from media resources
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Issues/Problems with Unit of Analysis
Ecological fallacy is one of the problems with units of analysis
Ecological fallacy refers to the danger of making assertions about individuals as a unit of analysis based on the examination of groups or aggregations (Poor areas = more crime, therefore poor people commit more crime)
Individualistic fallacy: danger of using hearsay/subjective evidence to make arguments about individuals
Eg. media stories about drug problems in US cities often focus on drug use among African Americans
That does not mean that most African Americans are drug users or that drugs are not a problem among Whites
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Time Dimension
Another dimension of research is the treatment of time
The time dimension of research requires careful planning
Observations can either be made more or less at one point, or stretched over a longer period
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Cross-Sectional Studies
Cross-sectional studies: observing a single point in time and analyzing that cross section carefully
Simple and least costly way to conduct research
A single US census, is a study aimed at describing the US population at a given time
A police dept study may ask residents about crime problems in their neighborhood in a single time frame
Problems: We cannot see social changes; have to worry if we picked a bad point in time to capture
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Longitudinal Studies
Longitudinal studies: permit observations over an extended time, ex. analyses of monthly drug arrests for 5 years
3 types of longitudinal studies –
Trend – studies changes within some general population over time. Eg. comparison of UCR figures over time, it may show an increase from 1960-1995 & a decrease pattern thru 2015
Cohort (age group) – examine more specific populations as they change over time. Could be age group
Cohorts are group of people who enter or leave an institution at the same time
Panel – similar to trend or cohort, but observations are made on the same set of people on two or more occasions (NCVS – subjects are interviewed 7times at 6 months intervals)
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Cincinnati Study on Lead Exposure
identify the type of study
Researchers at the University of Cincinnati recruited individuals born from 1979-1985 to take part in a study. During childhood, the research subjects’ blood was tested for lead exposure several times. Interviews and surveys of the subjects and their parents were used to assess the youths’ levels of delinquency. The results showed that youths who were exposed to lead engaged in more acts of delinquency and used marijuana more than those not exposed. At the time of this study, the research subjects were between 15 and 17. The researchers are still studying these subjects, which will allow for more examinations of the effects of lead exposure on adult behaviors.
Dietrich, K.N., Ris, M.D., Succop, P.A., Berger, O.G. & Bornschein, R.L. (2001). Early exposure to lead and juvenile delinquency. Neurotoxicology and Teratology, 23, 511-518.
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Answer
- longitudinal panel Study
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Approximating Longitudinal Studies
It is possible to draw conclusions about processes that take place over time even when only cross-sectional data are available
We can approximate longitudinal studies through logical inferences and retrospective studies
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Approximating Longitudinal Studies
Logical inferences: may be possible to draw approximate conclusions about processes that take place over time, even when only cross sectional data is available
Drawing conclusion about processes that take place across time
Eg. a researcher may discover in a cross-sectional study of high school students that males are more likely than females to smoke marijuana
The researcher can conclude that gender affects the tendency to use marijuana
i.e. drawing conclusion from a one-time observation to processes that take place across time
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Retrospective Research
Asks people to recall their past for the purpose of approximating observations over time
Eg. in a study of recidivism, we might select a group of prison inmates and analyze their history of delinquency or crime
Problems: People have faulty memories; people lie
Analysis of past records also suffer from problems – records may be unavailable, incomplete, or inaccurate
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Time Dimension Summarized
Cross-sectional study = snapshot – an image at one point in time
Trend study = slide show – a series of snapshots in sequence over time, allows us to tell how some indicator varies over time
Panel study is like a motion picture that can capture moving images of the same individuals
– gives information about individual rates of offending over time
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END
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Does Drug Use Cause Crime?
Temporal order: which comes first?
A statistical relationship exists, but underlying causes affect both drug use and crime (IV threat)
Relationship between crime and drug use varies by type of drug
How will policy affect drug use and crime? A crackdown on all drugs among all populations will do little to reduce serious crime.
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Scientific Realism
- Scientific realism: bridges/links idiographic and nomothetic approaches to explanation by seeking to understand how casual mechanisms operate in specific contexts
- Scientific realism studies how other possible influences are involved in cause-and-effect relationships
- Contains elements of both idiographic and monothetic modes of explanation
- Traditional approaches try to isolate causal mechanisms from other possible influences
- But scientific realist approach views other possible influences as context in which causal mechanisms operate
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