Hello Everyone,
I am in a bit of a pickle, as I am involved in research on neurofeedback and am conducting a study on whether a ratio of electrical power (microvolts) decreases as a subject continues sessions of the neurofeedback. I have performed regression analysis on each subject (30 subjects) in my study and have gotten very low X variable coefficients (-.0145, -.0022). The X values represent session number (each participant completed 40 sessions) and the Y values are the different ratios of power (i.e. 3.2, 4.5). My P values are also very high for each X variable coefficient as well (0.16, 0.26). To put it frankly, is this data doomed and not able to be discussed in a research paper considering there were hardly any significant decreasing trends? I only got low P values for a couple of the participants' regression analysis. Is there something I can do the make the P value lower as I conduct the regression analysis? Is it not valid or sound to have a low P value and also a low X variable coefficient? I am new to statistics so any kind of guidance would help. I was hoping to see this ratio of power decrease in subjects and it's disappointing to see such high P values for every regression analysis. Thank you.
Best,
Tristan Sguigna
I am in a bit of a pickle, as I am involved in research on neurofeedback and am conducting a study on whether a ratio of electrical power (microvolts) decreases as a subject continues sessions of the neurofeedback. I have performed regression analysis on each subject (30 subjects) in my study and have gotten very low X variable coefficients (-.0145, -.0022). The X values represent session number (each participant completed 40 sessions) and the Y values are the different ratios of power (i.e. 3.2, 4.5). My P values are also very high for each X variable coefficient as well (0.16, 0.26). To put it frankly, is this data doomed and not able to be discussed in a research paper considering there were hardly any significant decreasing trends? I only got low P values for a couple of the participants' regression analysis. Is there something I can do the make the P value lower as I conduct the regression analysis? Is it not valid or sound to have a low P value and also a low X variable coefficient? I am new to statistics so any kind of guidance would help. I was hoping to see this ratio of power decrease in subjects and it's disappointing to see such high P values for every regression analysis. Thank you.
Best,
Tristan Sguigna