Help me understand this table: Unstandardized Logit Coefficient and Beta?

In summary, the conversation is about trying to understand a table on logistic regression measures, specifically the "Unstandardized Logit Coefficient" and "Beta". The higher these coefficients, the higher the turnout for a certain variable in the left-most column. The beta is the standardized version of the unstandardized logit coefficient. The chart alone does not provide enough information to fully understand the coefficients and further research is needed.
  • #1
guss
248
0
Hello, I am currently doing a project and trying to understand this table. I have a pretty good mathematical background but I know very little about statistics. Could someone explain, in simple terms, what this table is saying, specifically "Unstandardized Logit Coefficient" and "Beta"? Thanks so much!

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  • #3
Simon Bridge said:
They are logistic regression measures.
http://www.appstate.edu/~whiteheadjc/service/logit/intro.htm

Thanks. So, just so I'm clear, a higher unstandardized logit coefficient means what? And a higher beta means what?

I'm confused about the difference. It seems to me that both a higher unstandardized logit coefficient and a higher beta mean a higher turnout for a certain variable in the left-most column.
 
  • #4
Can't tell what they are measuring from the chart alone.
eg.

IV: "mudslinging", ULC -0.07(0.03) ... would appear to be saying that mudslinging in the campaign has a slight negative effect on voter turnout but what are we to make of:

IV: "tone of the commercials" ULC 0.12(0.06) ... ?? I mean, what does "tone" measure and how was that measure turned into a logit coefficient?

You should look to see what they are "coefficients" to.

Whatver they are: the beta would be the same as the ULC only with their statistics standardized to unit varience. eg. they are showing the same thing in the sense that bigger numbers mean favorable ratios for the IV. The standardized measures are usually more useful for comparing different IVs to each other.
 
  • #5
Simon Bridge said:
Can't tell what they are measuring from the chart alone.
eg.

IV: "mudslinging", ULC -0.07(0.03) ... would appear to be saying that mudslinging in the campaign has a slight negative effect on voter turnout but what are we to make of:

IV: "tone of the commercials" ULC 0.12(0.06) ... ?? I mean, what does "tone" measure and how was that measure turned into a logit coefficient?

You should look to see what they are "coefficients" to.

Whatver they are: the beta would be the same as the ULC only with their statistics standardized to unit varience. eg. they are showing the same thing in the sense that bigger numbers mean favorable ratios for the IV. The standardized measures are usually more useful for comparing different IVs to each other.

Thanks, that helps a lot. That's a good enough understanding for me right now, I'll look into what exactly those coefficients are. And yes, you are correct about what the chart is trying to say.
 

Related to Help me understand this table: Unstandardized Logit Coefficient and Beta?

What is a logit coefficient and beta?

A logit coefficient and beta are statistical measures commonly used in logistic regression analysis to determine the relationship between a set of independent variables and a binary outcome variable. The logit coefficient represents the change in the log odds of the outcome for a one-unit change in the independent variable, while beta represents the change in the odds of the outcome for a one-unit change in the independent variable.

Why is the logit coefficient and beta important?

The logit coefficient and beta are important because they provide insight into the strength and direction of the relationship between the independent variables and the binary outcome variable. They also allow for the comparison of the impact of different independent variables on the outcome variable.

How is the logit coefficient and beta calculated?

The logit coefficient and beta are calculated using a mathematical formula that involves taking the natural logarithm of the odds of the outcome variable and using linear regression to determine the impact of the independent variables on the log odds.

What does it mean if the logit coefficient and beta are positive?

A positive logit coefficient and beta indicate a positive relationship between the independent variable and the odds of the outcome variable. This means that as the independent variable increases, the odds of the outcome variable also increase.

What does it mean if the logit coefficient and beta are negative?

A negative logit coefficient and beta indicate a negative relationship between the independent variable and the odds of the outcome variable. This means that as the independent variable increases, the odds of the outcome variable decrease.

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