Psychology Research Methods: Correcting Statistical Errors Case Study

Introduction: Avoiding Errors in Psychological Research Methods

Task 1: Statistical Analysis of ADHD and Motor Impairments

The study of the complex nature of attention hyperactivity disorder (ADHD), which includes motor impairments in addition to cognitive and behavioral issues, has come to signify in recent years. The study evaluates the data based on the Jamovi software to find out the result of the test. There may be a connection between children's ADHD and poor motor coordination. By assembling two separate samples, one made up of kids with ADHD diagnosis and the other of kids without this, the study seeks to empirically evaluate this link. The Conners was a 3 ADHD rating scale, which offers a thorough assessment of behavioral manifestations and will be used to assess ADHD symptoms. The Developmental Coordination Dysfunction Assessment (DCD-Q), a par?nt-r?port?d instrument created to recognize and quantify motor issues in children, will also be used to assess motor coordination.

Discussion

The Statistical Analysis Of The Children

Figure 1: Descriptive analysis of the ADHD level

Interesting results were found in the study evaluating motor impairments in children who had and did not have ADHD. Children with ADHD had a male motor problems score of 0. 500, which was somewhat higher than the 0. 483 average score for children ?xp?ri?ncing ADHD. The two cohorts' standard deviations, however, were 0.502 for each, demonstrating a significant d?gr?? of score agr??m?nt. A statistical test like the t-test is required to d?t?rmin? the importance of these diff?r?nc?s. The statistical significance of the observed differences in male motor problem scores comparing the two groups would be assessed using the t-test. In contrast to children without ADHD, children with ADHD may be more likely to have motor problems if the t-test produces a significant result (Frost, 2021). It is important to proc??d cautiously when evaluating these results, understanding that further statistical significance is n??d?d before definitive inf?r?nc?s can be made. Further statistical studies, like ANOVA, should be investigated to look into any differences in motor challenges between kids with various learning disorders. Although the man differences suggest a potential connection between motor impairments and ADHD, a thorough statistical analysis is necessary to d?t?rmin? the reliability and ability to be g?n?raliz?d of these findings. A more compr?h?nsiv? knowledge of the detailed relationship between children's ADHD and motor skills will be possible with additional study and analysis.

Figure 2: Descriptive analysis of the ADHD level frequencies

The next table shows the pr?val?c? of motor problems and ADHD in an examination of 120 kids. Among them, 62 (51.7%) have motor issues, 60 (50%) have ADHD, and 58 (48.3%) have both two diagnoses. Even though this descriptive summary points to a possible relationship, statistical analysis is necessary to assess the relationship's significance. The chi-square test is necessary to thoroughly evaluate whether kids ?xp?ri?ning ADHD are more likely to ?xp?ri?nc? motor issues (Howitt & Cramer, 2020). To assess the ind?p?nd?nc? between ADHD and motor impairments, this test would contrast observed fr?qu?nci?s with anticipated fr?qu?nci?s. By calculating the predicted fr?qu?nci?s using the marginal totals, an initial level for comparison is ?stablish?d.

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Figure 3: Graphical representation of the ADHD level

The image that is supplied is a graph with bars that show how common motor issues are in people who have and do not have ADHD. N?v?rth?l?ss, the lack of legend and axis markings makes a thorough interpretation difficult (Privitera, 2022). It is difficult to understand the precise information the chart is trying to ?xpr?ss in its absence of a legend that clarifies color or pattern differences and without obvious clubs of the information the bars symbolize (counts, percent, etc.). Additional information is necessary to provide a compr?h?nsiv? description, such as the dimension labels identifying the variables th?ms?lv?s that are being measured along with the m?asur?m?nts in units of m?asur?m?nt (Thomas et al., 2022). Important background information could be supplied via a legend explaining the significance of each of the colors or designs in the bars. Comprehending the trustworthiness and reliability of the information provided depends critically on understanding the data source. Without these important details, an accurate assessment of the chart is impossible. To ensure a more precise and observant study of the association between ADHD and the major difficulties s??n in the image, a thorough summary is awaited that clarifies the visualization and implications of the data.

Figure 4: Graphical representation of the motor difficulty level

After normalizing the squared discrepancies b?tw??n the observed and predicted fr?qu?nci?s by the ?xp?ct?d frequency, the coefficient of the chi-square statistic is calculated. The d?gr??s of flexibility and s?l?ct?d level of significance are used to d?t?rmin? the critical value, which is then compared to this statistic (Shadjalilovna et al., 2022). The null hypothesis is dismissed, and there is a significant correlation between ADHD and motor impairments if the value of the chi-square statistic is greater than the crucial threshold. In contrast, one is unable to dismiss the null hypothesis if the statistic is beneath the critical value, indicating that there is not enough data to conclude that there is a meaningful link. A strong framework for comprehending the possible connection between children's motor issues and ADHD is provided by this methodical approach to statistical analysis.

Evaluation Of The Percentage Of Children

Based on the previous study, the percentage of children who get scores above 45 and have motor difficulties are analyzed in this section (Privitera, 2022). At first, the descriptive analysis is being evaluated by taking two variables, which are the motor difficulties and the conners3. From the descriptive analysis, the number of corners is counted with the children who have motor difficulties. From this analysis for finding the percentage, the Conner numbers should have counted with the positive response of the motor difficulties.

Figure 5: The descriptive analysis of two variables

Then, the percentage can be obtained by multiplying by 100. Here the children who have scored more than 45 are number 2 and have motor difficulties. The total count of the canners is 14. So the percentage of the children is 142, which is multiplied by 100.

The Factual Mistakes Made By Dr. House

The connection between the children who actively play electronic games and those diagnosed with symptoms of ADHD. Dr. House made some mistakes regarding the interpretation of the statistical analysis (Grahek et al. 2021). The effect of magnitude and the misinterpretation of the p values are the main reasons for his mistakes. Dr House got the wrong interpretation of the values of p; for this reason, it claims that children who are actively participating in electronic games are more likely to have the symptoms of ADHD. The possibilities of acquiring the data were observed under the presumption that there doesn't exist a true link b?tw??n the variables as measured by the p-value. When the value of p is greater than 0.05, it is not possible to reject the null assumption. This results in more probable outcomes of the chance. This cannot give any evidence for this assumption of who is playing video games and having the symptoms of ADHD. It only implies that random variation may be the reason for any differences that are observed.

The Statement Of Dr. House After Correcting The Mistakes

Dr House mentioned 0.25, which is misint?rpr?t?d, and this effect size is dependent on the phi parameter (φ). Φ is a measurement of the d?gr??, which can correlate between two binary variables. This measures as 0.25, which depicts a tiny effect. The reliability of the effect size can be measured by the variables which are different from one another. A modest ?ff?ct size suggests that the distinction in ADHD rats of diagnosis between the youngsters who play games on the computer and those who do not is quite minimal (Artner et al. 2021). These types of ?v?nts is statistically significant correlation is observed here. To address these concerns, the new statement indicates that there was no statistically significant link (p greater than the value of 0.05) and acknowledges the tiy ?ff?ct size (φ which equals 0. 25). It highlights that there may be a chance explanation for the observed diff?r?nc? and that it is not statistically significant. This detailed interpretation avoids making incorrect statements regarding the connection between children's computer game playing and ADHD valuations, giving a more accurate view of the study's findings.

Conclusion

In conclusion, it can be concluded that evidence of the results of the children who are diagnosed with ADHD disease helps to implement the value of p. The scores of the developmental coordination disorder questionnaire enable the investigator to identify the difficulties in the sensory regions. There are two types of studies investigating children who have been diagnosed with the disease. The analysis is completely evaluated with the help of the Jamovi software in study one. In Study 2, House indicates the value of p which emphasizes Study One and the result based on this evaluates the mistakes that he been made by him.

References

Journals

• Frost, N. (2021). Qualitative research methods in psychology: Combining core approaches 2e. McGraw-Hill Education (UK). [Retreived From: http://psikologi.unmuha.ac.id/wp-content/uploads/2020/02/Qualitative-Research-Methods-in-Psychology.pdf][Retreived on: 8.12.2023]
• Howitt, D., & Cramer, D. (2020). Research methods in psychology. Harlow: Pearson. [Retreived From: https://www.academia.edu/download/32273923/INRODUCTION_TO_RESEARCH_METHODS_IN_PSYCHLOGY_(1).pdf][Retreived on: 8.12.2023]
• Thomas, J. R., Martin, P., Etnier, J. L., & Silverman, S. J. (2022). Research methods in physical activity. Human kinetics.[Retreived From:https://www.researchgate.net/profile/Jerry-Thomas-5/publication/229071220_Research_Methods_in_Physical_Activity/links/56deeb4708ae6a46a18497f5/Research-Methods-in-Physical-Activity.pdf][Retreived on: 8.12.2023]
• Shadjalilovna, S. M., Malikovna, K. R. N., Mirsharapovna, S. Z., & Kakhramonovich, A. A. (2022). Determination of the Needs of Students by Psychological and Pedagogical Teaching Tools Using Remote Technologies. Texas Journal of Multidisciplinary Studies, 14, 5-8. [Retrieved From: https://zienjournals.com/index.php/tjm/article/download/2642/2215][Retrieved on: 8.12.2023]
• Privitera, G. J. (2022). Research methods for the behavioral sciences. Sage Publications.[Retreived From: https://toc.library.ethz.ch/objects/pdf03/e01_978-1-5063-2657-3_01.pdf][Retreived on: 8.12.2023]
• Grahek, I., Schaller, M., & Tackett, J. L. (2021). Anatomy of a psychological theory: Integrating construct-validation and computational-modeling methods to advance theorizing. Perspectives on Psychological Science, 16(4), 803-815.[Retrieved From: http://www2.psych.ubc.ca/~schaller/GrahekSchallerTackett-PPS.pdf][Retreived on: 8.12.2023]
• Artner, R., Verliefde, T., Steegen, S., Gomes, S., Traets, F., Tuerlinckx, F., & Vanpaemel, W. (2021). The reproducibility of statistical results in psychological research: An investigation using unpublished raw data. Psychological Methods, 26(5), 527. . [Retreived From :https://www.researchgate.net/profile/Thomas-Verliefde/publication/346866695_The_reproducibility_of_statistical_results_in_psychological_research_An_investigation_using_unpublished_raw_data/links/60acf04e458515bfb09f1d28/The-reproducibility-of-statistical-results-in-psychological-research-An-investigation-using-unpublished-raw-data.pdf :][Retreived on: 8.12.2023]