Abstract
It is practically impossible to avoid losing data in the course of an investigation, and it has been proven that the consequences can reach such magnitude that they could even invalidate the results of the study. This paper describes some of the most likely causes of missing data in research in the field of clinical psychology and the consequences they may have on statistical and substantive inferences. When it is necessary to recover the missing information, analyzing the data can become extremely complex. We summarize the experts' recommendations regarding the most powerful procedures for performing this task, the advantages each one has over the others, the elements that can or should influence our choice, and the procedures that are not a recommended option except in very exceptional cases. We conclude by offering four pieces of advice, on which all the experts agree and to which we must attend at all times in order to proceed with the greatest possible success. Finally, we show the pernicious effects produced by missing data on the statistical result and on the substantive or clinical conclusions. For this purpose we have planned to lose data in different percentage rates under two mechanisms of loss of data, MCAR and MAR in the complete data set of two very different real researchs, and we proceed to analyze the set of the available data, listwise deletion. One study is carried out using a quasi-experimental non-equivalent control group design, and another study using a experimental design completely randomized
Highlights
Derived From the Analysis With the Complete Data The results obtained with the complete data in these three variables give us the same results as in the original research, and can be conclude that ACT may be an alternative to cognitive-behavioral therapy (CBT) for treatment of drug abuse and associated mental disorders
Data Analysis We examined the consequences of the data loss according to McL in both PdL on the empirical result of four statistics provided by the ANOVAChS model, mean square error (MSe), F, η2, and DM, in the same way as we did in the first research
In the MCAR condition with PdL 30% we would conclude that GC remains almost as at the beginning, in the may be at random (MAR) condition with PdL 10% we would conclude that ACT gets worse, and in the MAR condition with PdL 30%, we would conclude that the three groups practically behave in the same way
Summary
The two groups that received therapy experienced a statistically significant change [FPC = 6.84; gl = 47; η2 = 0.225; p = 0.002; 1-β = 904] to a greater extent CBT, distancing themselves from CG, whose condition got worse. At 6-months follow-up, ANOVAChS shows that ACT continues to improve significantly [FPC = 2.70; gl = 39; η2 = 0.122; p = 0.080; 1-β = 504]. CG does not get worse with respect to post-treatment. CBT experiences a tendency to return to baseline after the 6-month treatment completion
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
