How I can use regression analysis? ]]>

I have a general regression question. Is there an issue with doing a logistic regression with both positive and negative values in the independent variables?

I am looking to do the regression on entrepreneurial behavior from first to last business. For example, did the entrepreneur do more promos in the first or the last business? I basically subtract the values. So if he did more promos, the number will be positive, if he did less promos, then it would be a negative number (for example 10 promos in the first business but only 7 in the last business, it would be -3).

The dependent variable is success, coded as 1 for success and 0 for failure.

I've already done the regression but then it occurred to me that negative values may not be allowed? Is it okay to do the logisitic regression if the independent variables are compromised of both positive and negative numbers?

Many thanks! :) ]]>

My bachelor thesis is about fatigue, nausea and cognitive decline in patients who have head and neck radiation. For example, the dependent variable is fatigue, looked at the difference score (score of fatigue 6 months after radiation (T1) - the start of radiation (T0) score.

The multivariable analysis included:

* T0, as a separate variable, due to the expectation that the relationship between the variable and the endpoint Δfatigue may be different between patients with a low or high score at T0

* Chemotherapy

* WHO-score, as a confounder

My questions are:

- Should I look at the adjusted R2 when all variables are included in the analysis, or look at the adjusted R2 without the confounder in the analysis?

And if you want to look at the R2 of all variables in the analysis (including the confounder), the adjusted R2 is 26%

- Does this indicate that the difference between the patients, whether or not fatigue (the declared variance), is explained by 26% by chemotherapy alone? Because the WHO-score in the analysis is taken as a confounder?

Thanks for the answers.

Regards,

Lisa ]]>