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Zearthios may find the following thread useful:
http://forums.eviews.com/viewtopic.php?t=362&f=4.
Kind regards,
Carlo

Qbert123: my previous reply referred to an instance when the survey was not started out yet. Now I see that your query had a different flavour. An interesting textbook covering this (and related issues about dealing with missing vlues) is: Van Buuren, S. (2012), Flexible Imputation of Missing Data. ...

Rodcamb:
assuming you have one wave of data only and the relationship between depvar and indepvars is linear, OLS is the way to go.
Obviously you can add square-terms (or higher) if they fit your data better, as in OLS the assumption of linearity concerns coefficients, not variables.

Siroos: there's something that I don't understand about your query: If the same dummy is used to split time in 6-23 and 24-5 periods, you should have something like: dummy=0 if time ranges from 6 to 23; dummy=1 otherwise. But if you plug in among predictors two dummies (each representing one of the ...

Qbert123 raises an interesting issue. However, as far as her/his example are concerned, the risk of non-ignorable missing values can be avoided (or at least reduced) by fine-tuning the inclusion criteria in the study or improving the questionnaire items to be administered to participants. Kind regar...

Eleo: two remarks about your query: - I would keep the constant in the model. The fact the it is not significant is not self-explaining in itself, as it may depend on what does it refer to in your model. Moreover, I would test if the constant is still unsignificant after centering the predictors aro...

Sreeja,
it's hard to advise on your query with so scant details.
First off, what is your regression model? Simple or multiple OLS?

Kind regards,
Carlo

Tarox: - you can visually inspect your data distribution and check whether or not it is (or approaches) a normal one. However, as per the details you give, this would not seem the case. - should your raw data be not normally distributed you can consider performing a bootstrap ttest on untransformed ...

I'm not clear with your approach if your regresion setting is the linear one. Conversely, if you are talking about a logistic regression a yes/no dependent variable makes sense. However, the interpretation of your results could be easier if you convert the dependent variable into an odds ratio. Kind...