Response Guidelines

Provide a substantive contribution that advances the discussion in a meaningful way by identifying strengths of the posting, challenging assumptions, and asking clarifying questions. Your response is expected to reference the assigned readings, as well as other theoretical, empirical, or professional literature to support your views and writings. Reference your sources using standard APA guidelines.

Peers have responded to:

Data Screening

For this discussion, identify the goals of data screening. Then discuss how you can identify and remedy the following:

• Errors in data entry.
• Outliers.
• Missing data.

PEER RESPONSE 1

Cait Bahr 

Warner (2013) discusses the many goals of data screening in Chapter 4 of Applied Statistics from Bivariate Through Multivariate Techniques. Most importantly, data screening is used to monitor problems that may occur in data analyses (Warner, 2013). In data screening, it is necessary to identify all errors in data collection, otherwise, the results and data will be skewed and therefore incorrect. Other goals of data screening include correcting data errors, determining what data is missing and finding extreme outliers (Warner, 2013). Data sampling needs to be addressed in most data entry because there are significant problems that can occur when processing data (Warner, 2013). Some notable problems with data include extreme outliers, missing data, errors in data entry, small sample sizes, and nonlinear relationships in the data (Warner, 2013).

When identifying and remedying issues in data entry it is incredibly important to fix errors in data entry, locate outliers and correct any missing data (Warner, 2013). In order to address errors in data entry, all of the data must first be completely proofread (Warner, 2013). To ensure that the correct data is being entered, it is wise to compare the data being entered to the original data from the experiment (Warner, 2013). Additionally, the numbers being entered should be also compared to logbooks in addition to being checked by multiple individuals (Warner, 2013). In data entry, outliers are normally numbers that are either too high or look unusual (out of place) (Warner, 2013). So outliers do not skew or create false data, many researchers remove outliers prior to data entry (Warner, 2013). Lastly, when there is missing data there are many ways to replace data (Warner, 2013). For one, SPSS allows researchers to find missing data in their application, system missing values (Warner, 2013). Rather than counting the missing data as a form of data, this software instead replaces the missing data with an estimated value or excludes the missing data completely (Warner, 2013). Regardless of how the missing data is corrected, researchers are suggested to report all missing data in their research findings summary (Warner, 2013).

Reference

Warner, R. M. (2013). Applied Statistics From Bivariate Through Multivariate Techniques (2nd ed.). Thousand Oakes, CA: SAGE Publications.

PEER RESPONSE 2

Teddrick McCreary 

What are the goals of data screening? When we are working with numbers and data, there can be many different errors, measurements, inconsistencies, missing values or outliers. It is important that when we are researching information regarding any population, we need to run preliminary analyses with the data collection (Warner, 2013).  For myself, I found it easier to understand by means of: data screening is the way to inspect the data collected for any errors and correct those errors before the final analysis. This is done by checking over the data, recognizing any outliers, and then dealing with any missing data.

How can I identify and fix errors in data entry, outliers, and missing data?

• Errors in data entry: That really can be avoided by knowing more about where you are getting your information, any experiments, and being aware that there may be errors (Warner, 2013).  For myself, with the fact that I collect much of my data through anecdotals. So I am in the classroom, observing and collecting data on frequencies of behaviors, new behaviors, or types of behaviors. One of the main factors of error in my data entry would be the issue of reactivity. Meaning, since I am there and they are aware of my presence, they may be acting different because I am there. This does happen because they can be very happy that I am there and act differently because of that, or on the other hand I could be making them more anxious then they are normally. Either way, this is going to give me different numbers than if I were just to leave it to the staff to collect and document the data I need.

• Outliers: An outlier is data that is extremely different than what others are in the same sample, population, or individuals being surveyed (Warner, 2013). An outlier can be significant due to alerting the researcher that there is an abnormality or an error in the measurements that one is working on. When we find that we have an outlier, we then need to decide if we want to keep or take out the outlier. There are sometimes in which it would be ok to not add the outlier; however, there are times in which this outlier could be showing us a new trend or discovery in the information that we are looking at.

• Missing Data: Typically, we are not going to find the missing data until we enter the information into SPSS. Once we have entered the data, then there are two types of missing data, system missing and human error (Warner, 2013). We can do somethings with missing data. One thing we can do is just leave it alone. The missing values could be small, non-random, or something that we could just create a composite of the item by averaging them together into a new variable. One thing that we have to keep in mind is that with this missing data, SPSS with either use a listwise or pairwise deletion. Another thing we could do is delete the cases with the missing values, this way we have complete data for all of the subjects in the study (Psychwiki, 2011).

References

Psychwiki. (2011). Dealing with Missing Data. Retrieved from Psychwiki.com: http://www.psychwiki.com/wiki/Dealing_with_Missing_Data

Warner, R. M. (2013). Applied Statistics: From Bivariate Through Multivariate Techniques (2nd ed.). Thousand Oaks, CA: Sage.

My Initial Response:

Data Screening

The goals of data screening include:

• To check for outliers
• To check for missing data
• To check  for errors in data entry

Outliers can be spotted by either plotting a box/plot or a histogram of the variable. They can be corrected by omitting them in the analysis.

Missing data can be identified by exploring through your data set before commencing analysis. You can opt to delete the missing cases all together or fill in a value like the mean if deletion will result in sample size quality.

Errors in data entry can be spotted by either exploring your data set before analysis, counter checking with the source data or plotting a histogram and checking for inconsistent values. This error can be avoided by one been keen using data entry or using digital data capture media.

References

Warner, R. M. (2013). Applied Statistics From Bivariate Through Multivariate Techniques (2nd ed.). Thousand Oakes, CA: SAGE Publications.

Ethical and Professional Issues in Psychology Testing

Prior to beginning work on this assignment, please read the required textbook chapters and articles for this week.

Create a PowerPoint presentation with 16 to 20 slides (not including the title and reference slides) entitled Ethical and Professional Issues in Psychological Testing.  Your presentation must provide 2 to 3 slides for each of the required  topics and include appropriate citations of your referenced sources.  Separate reference slides, which follow APA formatting guidelines for a  References page, must be included at the end of the presentation. You  must create your own template and organize your presentation in the  sequence provided. Do not use a font smaller than 20 pt. You are  encouraged to insert relevant figures and graphics. Make sure to  appropriately cite any images you use. If you include a table or figure  from a journal article, cite it according to APA guidelines. The notes  section of each slide must include the text for oral comments you would  make while presentating the materials to a live audience.

References must be cited according to APA guidelines as outlined in the Ashford Writing Center (Links to an external site.)Links to an external site.. For assistance with creating a visually engaging and readable presentation, you may review Garr Reynolds’s tips for creating presentations (Links to an external site.)Links to an external site..

The presentation must cover each of the following topics in the order presented below.

The Ethical and Social Implications of Testing

• Provide an overview and brief evaluation of the ethical and social implications of psychological assessment.

Professional Responsibilities

• Describe the responsibilities of both test publishers and test users.

Testing Individuals Representing Cultural and Linguistic Diversity

• Analyze and describe issues related to the testing of cultural and linguistic minorities.

Reliability

• Explain the common sources of measurement error and how measurement error can impact reliability.

Validity  

• Create a diagram or figure to compare the types of validity discussed in the textbook.
• Describe the extravalidity concerns related to testing.
• Review the articles by Fergus (2013), Kosson, et al. (2013) and  Mathieu, Hare, Jones, Babiak, & Neumann (2013). Analyze the  information presented in these articles on factor analysis and describe  how it is used to validate the constructs of the instruments.

Clinical Versus Statistical Prediction

• Compare clinical and statistical prediction of mental health  decisions based on the work of Ægisdóttir, et al. (2006) and Grove &  Lloyd (2006).

Application One: An Ethical and Professional Quandry

• Select one of the Ethical and Professional Quandries in Testing from  Case Exhibit 1.2 in your textbook and describe the ethical issues  specific to the scenario you selected. Include an analysis of the  relevant principles from Standard 9 in the APA Ethical Principles of Psychologists and Code of Conduct (Links to an external site.)Links to an external site.
• Taking on the role of the psychologist or counselor in the chosen  scenario, describe how you might respond to the challenge you selected  and provide a brief rationale for your decision.

Application Two: Evidence-Based Medicine

• Summarize Youngstrom’s (2013) recommendations for linking assessment  directly to clinical decision making in evidence-based medicine.
• Elaborate on each of Youngstrom’s recommendations by providing  practical examples that illustrate the relevance of the recommendations  in a clinical setting.

Application Three: Selecting Valid Instruments

• Create a research hypothesis or brief clinical case scenario in  which you must select an instrument to measure intolerance for  uncertainty.
• Use the information in the Fergus (2013) article to support which measure to use.

The presentation

• Must consist of 16 to 20 slides (not including title and reference  slides) that are formatted according to APA style as outlined in the Ashford Writing Center (Links to an external site.)Links to an external site..
• Must include a separate title slide with the following:
  • Title of presentation
  • Student’s name
  • Course name and number
  • Instructor’s name
  • Date submitted
• Must use the assigned chapters in the course text, Standard 9 from  the American Psychological Association’s Ethical Principles of  Psychologists and Code of Conduct, and the 3 required peer-reviewed  articles assigned for Week One.
• Must document all sources in APA style as outlined in the Ashford Writing Center.
• Must include separate reference slides formatted according to APA style as outlined in the Ashford Writing Center.

Carefully review the Grading Rubric (Links to an external site.)Links to an external site. for the criteria that will be used to evaluate your assignment.