0 ×

Deprecated**KNIME Statistic Nodes (Labs)** version **4.1.1.v202001312018** by **KNIME AG, Zurich, Switzerland**

This node calculates the Maximum Likelihood Estimate (MLE) Odds Ratio (OR) and the Maximum Likelihood Estimate (MLE) Risk Ratio (RR), i.e., "Wald" OR and RR, from two selected categorical columns. For each column a value is selected to be considered the value under observation. All other values in non-binary categorical columns are considered as the "not" case.

X | ¬ X | |
---|---|---|

Y | a | b |

¬ Y | c | d |

Odds Ratio:

OR = (a/b) / (c/d) = (a * d) / (b * c)

Risk Ratio:

RR = (a / (a+b)) / (c / (c+d))

**Fisher's Exact Test** is calculated with

p = (a + b)!(c + d)!(a + c)!(b + d)! / (a!b!c!d!n!), where

n = a + b + c + d

over the sum of the marginal tables.

The two-tailed, left-tailed, and right-tailed p-values are calculated. The value for the Laplace correction is not considered for this calculation.

The **Chi-Squared Test** (**Χ**^{2}) is calculated with

Χ^{2} = ∑_{i} ∑_{j} (O_{ij} - E_{ij})^{2} / E_{ij}^{2}

where

E_{ij} = T_{i} * T_{j}/n

and

T_{i} and T_{j} are the sums of the row and columns respectively.

**Yates' Corrected Χ**^{2} is

Χ^{2}_{Yates} = ∑_{i} ∑_{j} (|O_{ij} - E_{ij}|-0.5)^{2} / E_{ij}^{2}

**Pearson's Coefficient of Contingency**

Pearson's C = √Χ^{2} / (Χ^{2} + n)

**Cramér's Coefficient of Contingency**

Cramér's V = √Χ^{2}/n

- Column X
- The column to choose for the X variable.
- Column Y
- The column to choose for the Y variable.
- Value from Column X
- The value from the X variable to choose as the value to be examined.
- Value from Column Y
- The value from the Y variable to choose as the value to be examined.
- Confidence Interval
- The confidence interval to be calculated.
- Laplace Correction
- The amount of Laplace correction to use, if one of the values ({a,b,c,d}) is 0. This value is applied to all four entries in the contingency table.

- The output table with the results and significance measurements.
- A table with the values from the table shown above.

- Java Snippet (9 %) Streamable
- Decision Tree Predictor (9 %)
- MultiLayerPerceptron Predictor (9 %) Streamable
~~Logistic Regression Learner~~(9 %) Deprecated~~Regression Predictor~~(9 %) Deprecated- Scorer (9 %)
~~Number To String~~(9 %) Deprecated- Domain Calculator (9 %)
- Column Filter (9 %) Streamable
- GroupBy (9 %)
~~XLS Reader~~(9 %) Deprecated- Show all 11 recommendations

To use this node in KNIME, install KNIME Statistics Nodes (Labs) from the following update site:

KNIME 4.1

A zipped version of the software site can be downloaded here. Read our FAQs to get instructions about how to install nodes from a zipped update site.

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter, or chat on Gitter!

Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.