Good Example Of Research Paper On Research Designs

The classic experimental design

It is imperative to mull over the impact of rival causal factors in a study. The threats that these factors pose diminish the efforts of a researcher who is seeking to maintain accuracy of their data. Factors such as history and maturation increase the level of biasness consequently leading to invalidity in the content of a study. Research designs, therefore, seek to minimize the effect of these errors.
In eliminating the probability of error, the classical experimental design takes into account three elements namely; equivalence, control groups and pretests (and posttests). Equivalence defines the researcher's role in selecting respondents and grouping them according to appropriate factors. It is crucial for the researcher to assume that the groups are similar and for this reason, comparable.
Two major methods are used in ensuring efficiency in equivalence. Randomization ensures that a researcher freely assigns subjects into groups. With this method, every person has an equal chance to get into the designated groups. A researcher may either select individuals without a particular order or use samples from the given population depending on its size. Matching supports equivalence by choosing subjects according to key characteristics such as their gender, age, or race. Although the method seeks to group individuals with similarities, it can as well work within randomization in achieving equivalence.
After ensuring that the groups are sufficiently similar and fair, it is vital to expose them to protests or observations and post-tests. Pretests and post-tests are measurement tools that determine the validity or effectiveness of the groups in ensuring they are free from biases. Exposing the group to the final predictor variable is experimental grouping. The rest of the groups are placed under control grouping.

Example

The National Center for Technology Innovation used an example quasi-experimental study. A quasi-experimental study seeks to determine the success of an intended action of intervention on participants. It includes; pretest and post-test designs, a treatment, and control group and randomization in assigning study participants
The halo effect is a common rival causal factor evident in this study. It reveals the biases depicted by observers during the study. The bias observers unintentionally release information based on experiences or prior information rather than their first-hand observation. To reduce the likelihood of occurrence of the halo effect, the researcher needs to rate specifically and expose the variable. The researcher's biases may also interrupt and influence the data collection. Losing the accuracy of the data due to ignoring information that one is not acquitted and conversant with, is natural and eminent.
History is a major factor contributing to interference invalidity of the data. A researcher may either select individuals without a particular order or use samples from the given population depending on its size. Matching, on the other hand, supports equivalence by choosing subjects according to key characteristics such as their gender, age, or race. Although the method seeks to group individuals with similarities, it can also work within randomization in achieving equivalence.
Instrumentation error is mainly due to changes made to the measurement instruments during the study – Instruments such as interviews, questionnaires, and observation techniques. The researcher should maintain rather than change the techniques of gathering data. It is because some of the respondents are not familiar or very effective with some techniques of data gathering.
Testing biases describes the information available to respondents prior to the study. This unintentional spilling of information is due to pretests that avail the knowledge of important areas of concern. Respondents end up giving information basing on their knowledge of the tests rather than their first-hand experience. This knowledge leads to biases and consequently, the loss of validity on the results.

Why are time-series designs particularly useful in criminal justice studies?

Time-series designs are studies that focus on only one variable such as crime. Using records of both before, and after the appropriate taking an action; time series designs accurately determine reliable statistics vital in prediction. The accuracy is extremely important in criminal justice.
As types of a longitudinal study, time-series designs focus on a particular group's timely observations. The observations are based on measurements over a specified period. The design study involves measuring only one variable at a time.
There are different types of time-series designs. An Interrupted time-series design focuses on taking measurements at specified time points before intervention and for another specified time (often-equivalent period) after the intervention. In the instance of crime, it is easy to read and notice the effects of the proposed solution, as well as predict the future basing on the rate of improvements and in accordance with the regular periods.
Counter-crime departments are often criticized for spending most of their available funds on longitudinal studies such as time-series designs. The designs are vital in exposing and reviewing the progress and success of corrective measures. The results also indicate the future trends of crime rates are consequently creating an opportunity for future solutions.
Criminal justice departments continue to employ the services of time-series designs to study trends in crime today. These study methods are more accurate than other traditional methods as they employ methods to reduce errors and biases in the results.
Multiple interrupted time-series designs, unlike single interrupted time-series designs (considering those only as one group), effectively contrast and compare two groups. For instance, they compare the performance of a group to that of others with previously recorded analyzes. They, for this reason, offer a wider range of options and results useful in solving crime.

A hypothetical study

Crime in a poor neighborhood in the suburbs of a southern American city has consistently topped the major areas prone to crime. Several actions have failed to eliminate completely or considerably reduce crime in the area. The police have recorded all the efforts they have employed in seeking to minimize the rates of crime among the stubborn citizens.

The Kansas City gun experiment

In the Kansas City preventive patrol study, the researchers employed the classic experimental design to determine the best control. Using matching method to ensure equivalence, the officers divided the sample recipients into two groups.
Findings of the study revealed that unemployed people constituted most of the people involved in crime. Unemployed people made the majority of the population of City dwellers. These high levels of unemployment caused the rapid rise in crime rates. Another report revealed that two-thirds of the criminals never married. Approximately 60% of the suspects previously went to jail on accounts of incrimination for similar offenses.