Component #2 – Literature Review (4 pages) 

Literature Review: Combine what researchers have found on your topic. What researchers believes, disagree on, similarities, etc.  This is the basic understanding as to what has been stated about your topic.  You examine within your journals different methods/ research designs that the research developed to prove or answer your thesis question.  A perfect way to set up this section is take articles that have similar methods and compare them to each other. Again, try to find methods that you would like to use in your own study. For example, if you plan on conducting a randomized experiment find articles on other randomized experiments and discuss their strengths and weakness.

A literature review is a review of what other researchers have found on your topic. Literature reviews are found in the beginning of most journal articles. In order to have a well compiled literature review, you will need at least (5) journal articles. Some great examples of journals are:

• International Journal of Comparative and Applied Criminal Justice.
• Journal of Criminology: Wiley-Blackwell
• Journal of Crime and Delinquency: Sage
• Criminal Justice and Behavior: Sage
• Sexual Abuse: A Journal of Research and Treatment: Sage
• Journal of Criminal Law and Criminology: Northwestern University School of Law
• British Journal of Criminology: Oxford University Press
• Journal of Research in crime and Delinquency: Sage
• Journal of Quantitative Criminology: Springer
• Punishment & Society: Sage
• Journal of Interpersonal Violence: Sage

The Elements of a Literature Review:

• A brief overview of the topic at hand, different issues that other researchers have found about the topic, or explaining the use of different theories under consideration.
• Sometimes block format is used where the writer explains those in support of a certain position and then a paragraph of those against, even offering an alternative position can be useful.
• Explaining the similarities and the difference of the research can be useful. It is very important to explain the variations of what different researchers have found about your topic. This allows the reader to see what has already been stated about your topic and therefore can help develop a path to where you the writer wants to take your topic.

A few important points to remember about a literature review, is that one sentence may cite several sources. Throughout this section you are combined what the researchers have previously found. Therefore, you need to incorporate more then one author per paragraph.

For each of the (5) journal articles (Note: you do not need to format your other resources this way as they may be supplemental in nature, e.g. provides statistical information): 

• Theory:
• Hypothesis:
• Variables (Dependent and Independent)
• Type of Design:
• Sampling Technique:
• Sample Size/Details:
• Results
• Critique/Limitations:
• How this article relates to your design:

Example

           Walfield (2008) and Clarke (2010) have cited very interesting information on the topic of wrongful convictions. Although they both believe that wrongful convictions are not a product of the crime control model their reasoning behind their beliefs differs… (THIS IS JUST AN EXAMPLE) (Please see attachment with real literature review examples). A simple explanation is to take different articles and compare them and contrast them, again explaining what has been cited about your topic.

Sampling
Chapter 6

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Introduction
Sampling is the process of selecting observations
Often not possible to collect information from all units you wish to study
Often not necessary to collect data from everyone out there
Allows researcher to make a small subset of observations and then generalize to the rest of the population

The Logic of Probability Sampling
Samples: a group of subjects selected from a population
Probability sampling: a method of selection in which each member of a population has a known chance of being selected
Enables us to generalize findings from observing cases to a larger unobserved population
Because we are not completely homogeneous, our sample must be representative of the variations that exist among us

Conscious and Unconscious Sampling Bias
Be conscious of bias – when sample is not fully representative of the larger population from which it was selected
Sampling bias is not always obvious
Use techniques to help avoid bias

Representativeness and Probability of Selection
A sample is representative of the population from which it is selected if the aggregate characteristics of the sample closely approximate the same aggregate characteristics in the population
Samples that are representative of the population are often labeled equal probability of section method (EPSEM) samples because all members of the population have an equal chance of being included in the sample

Sampling Terminology 1
Sample Element: who or what are we studying (student)
Population: whole group (college freshmen)
Population Parameter: summary description of a given variable in a population
Sample Statistic: summary description of a given variable in a sample; we use sample statistics to make estimates or inferences of population parameters

Sampling Terminology 2
Sampling distribution: a range of sample statistics we obtain if we select many samples from a population
Sampling frame: actual list of units to be selected (our school’s enrollment list)
Binomial variable: a variable with only two values

Sampling Terminology 3
Standard error: a measure of sampling error; we can estimate the degree to be expected
Confidence Levels and Confidence Intervals
Two key components of sampling error
We express the accuracy of our sample statistics in terms of a level of confidence that the statistics fall within a specified interval from the parameter

Sampling Designs 1
Simple Random Sampling: each element in a sampling frame is assigned a number, choices are then made through random number generation as to which elements will be included in your sample
Systematic Sampling: elements in the total list are chosen (systematically) for inclusion in the sample
List of 10,000 elements, we want a sample of 1,000, select every tenth element
Choose first element randomly

Sampling Designs 2
Stratification: modification to random and systematic sampling; ensures that appropriate numbers are drawn from homogeneous subsets of that population
Disproportionate stratified sampling: way of obtaining sufficient number of rare cases by selecting a disproportionate number
Cluster sampling: compile a stratified group (cluster), sample it, then subsample that set
This process can go on for many cluster levels

National Crime Victimization Survey
Seeks to represent the nationwide population of persons 12+ living in households (≈ 42K units, 74K occupants in 2004)
First defined are primary sampling units (PSUs)
Largest are automatically included, smaller ones are stratified by size, population density, reported crimes, and other variables into about 150 strata
Census enumeration districts are selected (CED)
Clusters of 4 housing units from each CED are selected

British Crime Survey
First stage – 289 Parliamentary constituencies, stratified by geographic area and population density
Two sample points were selected, which were divided into four segments with equal #’s of delivery addresses
One of these four segments was selected at random, then disproportionate sampling was conducted to obtain a greater number of inner-city respondents
Household residents aged 16+ were listed, and one was randomly selected by interviewers (n=37,213 in 2004)

Nonprobability Sampling
Nonprobability Sampling: the likelihood any element will be include in the sample is unknown
Purposive sampling: selecting a sample on the basis of your judgment and the purpose of the study
Quota sampling: units are selected so that total sample has the same distribution of characteristics as are assumed to exist in the population being studied
Snowball sampling: You interview some individuals, and then ask them to identify others who will participate in the study, who ask others…etc., etc.

Example: Snowball Sampling
To study cannabis users, Hammersley and Leon (2006) gathered a snowball sample of 176 University students who had used marijuana at least once. Extensive interviews were then conducted with the University students in the sample. Their results showed that there were two types of users—those who used cannabis on a regular basis and those who used cannabis on occasion. The results also showed that users experienced both positive and negative effects from using marijuana and the patterns of use were more similar to patterns of alcohol and tobacco use than to patterns of controlled substance use.
Hammersley, R. & Leon, V. (2006). Patterns of cannabis use and positive and negative experiences of use amongst university students. Addiction Research and Theory, 14(2), 189-205.