Gilad Sabo

When presenting a unified gray display, strongly illuminated, an illusion of dark line in the middle of it is present. Can one explain why? Is it another instance of lateral inhibition or is it something that goes beyond that?

Hi to all,

I graduated MA in cognitive psychology degree about 7 years ago and wrote two academic papers ever since, I was PhD student for one year (studying numerical cognition) and though it was of huge interest for me things didn't go well then.

I always have new ideas for study and currently very interested in the topics from environmental psychology. Some of the studies I have in mind do not require lab and may be done, perhaps, independently.

But I think finding someone to cooperate with would be better idea. I don't mean to PhD supervisor/promoter, just someone from the academia (or independent researcher) to cooperate with. This is because the main objective is to do research and make it published in peer reviewed journals. I don't mind doing most of the work yet being second or third in the authors list.

I would be glad to get any ideas and/or offers in regard to how I can find someone to share ideas and do studies with.

Best regards,

Gilad

Hi,

I'm currently not affiliated with any research institution or group. I've though few theoretical ideas in cognitive and social psychology that I want to publish. These are ideas that I want to base on literature review  without any experimental work. 

I published two experimental works in the past (one in 2012 and one in press). But this time I'm not affiliated and basically I just wonder how can I publish this way, where and what would be the best way to push to it.

Best regards,

Gilad

Just wonder, 

What can be proper and validated task to evaluate in children aged 8-11 and adolescents aged  12-14

1. Executive functions.

2. Resourcefulness.

3. Initiation.

Now, I know there are inventories for these (like the BRIEF for executive functions) but I'm more interested in tasks, preferably the kind of tasks that don't consume more than 5-10 minutes per participant  and doesn't require expert to deliver them. 

Also, when it comes to executive functions I would like to know about tasks that evaluate attentional control, inhibitory control,  and cognitive flexibility, reasoning, problem solving, and planning and working memory each by itself or (and preferably) a combination. 

Thanks!

Hi all,

Just wanted to ask If I test how IVs A,B,C,D, E, F predict depended variable Y and given that: .

A is point in time (before or after manipulation).

B is the group to which participants belong (control or experiment).

C and D are two measures of well being. 

E and F are sex and age.

Y is measure for resilience.

Now, here is where it  become a bit complex, I assume that after manipulation there would be increase in scores of C and D for the experiment group but not for the control group. Also, C and D scores will positively predict Y scores for both control and experiment groups. Of importance, I assume that C and D will predict the same or higher level of the variance in Y scores and that Y scores therefore would be higher for the experiment group after the manipulation (no change in the control). No special predictions for sex and age, they are very much covariates. 

So, what analysis should I use?

You can find attached text file that summarize the outcome of three regression I took on data with continuous dependent variable and 5 IVs, one was dummy coded (sex) and the rest are continuous.

The reason I took ridge and lasso regression at the first place is because I had very strong co-linearity  between two of my independent variables. I also tried robust regression because it's immune to  violations of the assumptions of ordinary least squares regressions. 

So now I want to know which is better: A. to report on ridge+lasso regression outcome. or B. Robust regression outcome or C. both. 

Also, I would like to know if I need to add OLS regression analysis and if the answer is yes, would I have to add it penalty value?

Another question, and perhaps most important, how do I get adjusted R^2, adjusted R^2 change (if the output can only give pseudo ones, any other package in R that give real ones for all or part of these types of regression and how?), F values, significance level and etc from this output for each analysis?

Last question, should I report lambda values for ridge and lasso regression? Which of them, min? 1se? As for robust regression, should I report weights, if yes, how? Any other values that I should report? 

If you don't know how it goes for APA, any other format would be good to start with. Though the variables are all from social sciences.

Sorry for coming up with so many questions on the subject, it's just that I'm at the beginning of learning process on these subjects.

Hi,

I have data that is based on sample of children and adolescents aged between 10 to 14. When I checked my IVs (scores on few different tests) and my depended variable (score on a personality test) for normality they all appear to be non normal according to Shapiro-Wilk test though skewness and kurtosis values were pretty ok for most of them (smaller than 1 and close to 0.5). I tried to normalize the data (which include relatively many zero values that I thought were behind that non normality) using log10, inverse and sqr root methods (after adding 1 to all values). Non of them led the data to normality. I didn't try reflection because I fail to see how that may help and also I didn't try box cox because it only applies for the DV. 

I then tried to see the distribution when I divided the sample per age and per sex and the non normality gone. It seems that the strongest effect was of age. Meaning, my sample actually include three different populations- I didn't plan that, such significant differences were not predicted per age and sex.

The problem is that I really need to use regression and my sample size is not big enough to use only part of the data for that (I've nearly 300 participants but if you check them per age group and sex then we get six small groups of different sizes and considering I've 3 IVs, it's not a good idea). Is there anyway to normalize such data without dividing it to groups?

Hi all,

I'm using one scale with only three questions. It's creative uses questionnaire so the more adequate uses one count for each question the higher the score is for this question. 

The answers are then ranked for their originality (suitable answers that were given by less than 2% of the participants) fluency (how many solutions were given for each question) and flexibility (how many categories were created from the answers that were given by the participant for each questions).

I run reliability test for this three scores (originality, fluency and flexibility) between the three question items. Fluency and  flexibility had good Cronbach's alpha ~0.8. Originality was pretty low (~0.5). I then used factor analysis that extracted only one component of the three. The loading of the first two questions were high (~0.85)   but the third (Uniqthver as seen in the attached component matrix) didn't. 

Basically the originality score was the lowest (natural if you consider the strict criteria of defining answer as original) so to better understand I checked for frequencies and found out that while total of 30 original answers were given for  the third question, the two first only have ~20, plus they were more equally distributed among subjects (well, just from looking on the data).

So how should I continue now with the third question? I don't think that I can throw it (or the two first) but apparently they don't measure in the same way originality (or they do and only because of one extreme observation at the third question it seems like they don't, should I throw that observation then? Doesn't sound like good science).

This creativity test is one of my IVs so the question is important.