1. ## Binary logistic regression

Hi there
i ran logistic regression and got the following model:

var1:
B = -5.670
Sig = 0.01
Exp (B) 0.003

Constant:
B = -0.469

Since the B is negative, is it true to say that for every one unit increase in var1 there is a 99.7 (1-odds ratio) chance of a decrease in the outcome (in this case - no)?

var1 is expressed in proportions (0-1). what is considered one unit here?

K

2. ## Re: Binary logistic regression

X1 = B

For every 1 unit increase in X1 the odds of the outcome decrease by 0.3%. You can change the number of units to perhaps make this more meaningful.

What does the distribution of X1 look like? Can you upload a histogram of the variable?

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kasperski (08-02-2016)

4. ## Re: Binary logistic regression

Thanks so much!

5. ## Re: Binary logistic regression

Well, what I was looking for was where the values were landing between 0-1. When using a proportion it is bounded, so say you had most all values at around 90% or higher, interpretations are highly compromised along with confidence intervals. If your histogram is supposed to represent percentages you are probably fine putting var1 in the model, based on my limited knowledge.

Many programs let you set the value of units. If you don't know what the default is in your program, you can sent it to a value and see if the estimates are the same in both models.

Side note, if the program is using 1.00 as the unit and the variable is formatted as percent, then your results seem miniscule regardless of the p-value (e.g., for a 100% increase odds go down 0.3%. Do you get what I am saying?

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kasperski (08-02-2016)

7. ## Re: Binary logistic regression

totally get what you are saying. thanks again for your help!

8. ## Re: Binary logistic regression

I hate to bother you again, but i can't figure out what is the default value in SPSS or how it can be set...
thanks again

9. ## Re: Binary logistic regression

How is you variable formatted? If in decimals, you could reformat it to integers (multiple by 10) and see if estimates change. I think that would work??

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kasperski (08-03-2016)

11. ## Re: Binary logistic regression

well, when i turn the proportion to percentage (X100) the B changes to -0.057 and Exp(B) changes to 0.945.
that is, the B went from -5.7 to -0.057.

12. ## Re: Binary logistic regression

Well I usual just talk out my of rear, but mathematics prevailed. Now comes the question of which one do you use.

Unfortunately I appear to have been a bonehead before. The original interpretation was for a 100% unit increase in X1 the odds of outcome are 99.7% lower. Now we have for a 1% increase in X1 the odds of outcome are 5.5% lower. Do these jive with your hypothesized changes. Another option is to switch the outcome group so you predict the other group then you can say for every 1% increase in X1 the odds of other outcome are 5% (e.g., 1/0.9445)greater.

I guess you get what you pay for

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kasperski (08-03-2016)

14. ## Re: Binary logistic regression

that makes a lot of sense! i can't thank you enough!

15. ## Re: Binary logistic regression

No problem. I use logistic reg, kind of regularly, so these questions help me make sure I don't mess up my own analytics - just everybody else's.

Side note, you did not have any proportions in the lower or upper areas of 0-1. So you are limited when making statements to those values that were in your dataset, so say you can't extrapolate to 99%. Which should be intuitive, but we all forget things. Reason being you don't know if those values may have had a different effect in the model (not a linear relationship between 1-99 when using 1 unit increases). Does that make since (perhaps if you fall down 5% of the time it effects your outcome such and such way, but if you fall down 60% of times that 1 unit change isn't the same related to the outcome (you can't just generalize the !% increase because this people have a different odds of outcome). You can create other estimates based on data though, so you can plug values in your model equation and find the odds ratios for certain values say those with X1 = 20 versus 35.

16. ## Re: Binary logistic regression

well i did have .97, .88 and .85 and 22 more data point under .07, but i get what you are saying.
thanks again!

17. ## Re: Binary logistic regression

X1 = B For every one unit increase in X1 odds of a reduction of 0.3% results. You can change the number of units to be able to make this more meaningful. What does the distribution of X1 like? You can upload a graph of the variables?

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kasperski (08-08-2016)

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