What is the easier way to draw a study selection flow chart?

What is the credibility of a publication in cureus? In recent times a lot of students are publishing through Cureus. But it does not have an impact factor.. plus the peer review is also questionable.. any experiences?

1) Because I am a novice when it comes to reporting the results of a linear mixed models analysis, how do I report the fixed effect, including including the estimate, confidence interval, and p-value in addition to the size of the random effects. I am not sure how to report these in writing. For example, how do I report the confidence interval in APA format and how do I report the size of the random effects?

2) How do you determine the significance of the size of the random effects (i.e. how do you determine if the size of the random effects is too large and how do you determine the implications of that size)?

3) Our study consisted of 16 participants, 8 of which were assigned a technology with a privacy setting and 8 of which were not assigned a technology with a privacy setting. Survey data was collected weekly. Our fixed effect was whether or not participants were assigned the technology. Our random effects were week (for the 8-week study) and participant. How do I justify using a linear mixed model for this study design? Is it accurate to say that we used a linear mixed model to account for missing data (i.e. non-response; technology issues) and participant-level effects (i.e. how frequently each participant used the technology; differences in technology experience; high variability in each individual participant's responses to survey questions across the 8-week period). Is this a sufficient justification? 

I am very new to mixed models analyses, and I would appreciate some guidance. 

Hi everybody!

I have 2 groups (WT and KO) of indivuals for whom I obtain their weight each month during a year. The simple question I want to answer is: Do the WT group gain more (or less) weight that KO group over-time?. If true, at which time point /s is this difference significant?

For example:

GROUP M1 M2 M3 M4 M5 M7 M 8...

WT (5 indv) 5.8 5.9 6.9 7.8 12.1 14.5 20.9

KO (7 indv) 5.8 5-9 6.8 8.0 8.1 8.2 8.3

From these data it's clear that the WT group gains more weight that KO group. Moreover, I could say that the significant differences are in months 5 to 8....

I know this is a very recurrent experimental design and I have been looking for the correct statistical analysis to answer that question, but I found conflicting recomendations:

1) Repeated measures ANOVA, can show me differences between time-points of each group: The WT group has increased significantly from M4 to M5... (I am not interested in this kind of conclussions, or at least not only in this kind of conclussions) but it says nothing about differences between both groups.

2) Two-way ANOVA. I've been reading about the design of the experiments for which Two-way ANOVA. They look for the effects of 2 independent variables in an outcome. BUT! There is a big difference in the desing of the experiments that I have been reading for: "All the individiuals receive all the conditions (only chages the order)". THIS IS NOT MY CASE! The same occurs with two-way-reapeted-measures ANOVA!!! :(.

Further, as i'm interested in the difference in increases I think it should be better to work with weight changes (or percent changes). I mean, it can happen (for example) that WT group have higher weights from the beggining to the end than KO groups (resulting in statistical significant differences at all timepoints) but the increases are the same. For example:

GROUP M1 M2 M3 M4 M5 M7 M 8...

WT (5 indv) 20 30 40 50 60 70 80

WT (5 indv) 50 60 70 80 90 100 110

In these data (differences in absolute weights may be significant at all time-points) but both groups are increasing the same (10 gr per month) at all time-points....

Rather than absolute changes I can use relative changes..(In fact, I have also seen that ANCOVA is better for this kind of conclussions, since it takes into account the initial value and you can even represent the "corrected" changes).

As you can see.... I'm a mess!!!

I'm I wrong with my interpretation of two-way-ANOVA?

Which tests should be better for my question? Repeated measures ANCOVA??? mixed effects model? split-plot factorial analysis of variance? XD. which should be my post-hoc test?

I work in R...

Thanks in advanced!

The result of calculating effect size using Cohen's formula has generated an answer of:

-0.244750562

This corresponds to a medium size effect but it has a minus so how does this impact the answer?

Because someone told me that its reputation is not good.

Regression in academic research 

I'm going to use Pearson's correlation coefficient in order to investigate some correlations in my study. I've tested my data and I'm pretty sure that the distribution of my data is non-normal. My data are the cumulative incidence cases of a particular disease in 50 wards. Can I use Pearson's coefficient or not? (Link me to references if there be.)

I am looking for some citations for thumb rule for is there any thumb rule for I²-heterogeneity test in meta-analysis. Can anyone suggest some studies?

Hi, i am using multiple regression for one of my papers and i came across two types of B; B  and β, for which i don't understand the difference. Looking for answers in books and internet made it worse. Some say that β is the power, or similar to the alpha level, and some say that it is the beta weight. But if β is the beta weight, then what does the B stands for?

Thanks in advance