# What is C statistic in logistic regression?

## What is C statistic in logistic regression?

What is a C-Statistic? The concordance statistic is equal to the area under a ROC curve. The C-statistic (sometimes called the “concordance” statistic or C-index) is a measure of goodness of fit for binary outcomes in a logistic regression model.

Where is the odds ratio in SPSS logistic regression?

Logistic regression in SPSS We use the weight by command to weight our cases. Also, in the interest of saving space, we have included only the last of the tables that are presented in the SPSS output. The odds ratio is given in the right-most column labeled “Exp(B)”.

How do you interpret logistic regression in SPSS?

The steps for interpreting the SPSS output for a logistic regression

1. Scroll down to the Block 1: Method = Enter section of the output.
2. Look in the Omnibus Tests of Model Coefficients table, under the Sig.
3. Look in the Hosmer and Lemeshow Test table, under the Sig.

### Is C statistic same as AUC?

Harrel’s concordance index C is defined as the proportion of observations that the model can order correctly in terms of survival times. When censoring is observed the statistic only includes those patient pairs for which valid comparisons can be made. Sometimes C is called the AUC.

How is C Stat calculated?

The c-statistic is equal to the AUC (area under the curve), and can also be calculated by taking all possible pairs of individuals consisting of one individual who experienced a positive outcome and one individual who experienced a negative outcome.

What does C equal in statistics?

The superscript c means “complement” and Ac means all outcomes not in A. The complement of an event is the subset of outcomes in the sample space that are not in the event. A complement is itself an event.

#### How do you interpret a logistic regression analysis?

Interpret the key results for Binary Logistic Regression

1. Step 1: Determine whether the association between the response and the term is statistically significant.
2. Step 2: Understand the effects of the predictors.
3. Step 3: Determine how well the model fits your data.
4. Step 4: Determine whether the model does not fit the data.

What is C value in statistics?

The C statistic is interpreted as the probabil- ity that a randomly selected subject who experienced the outcome will have a higher predicted probability of having the outcome occur than a randomly selected subject who did not experience the outcome.

What does C stand for in stats?