You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["AnatomicalEntity"].

Please return the output as a JSON object of the format: {"AnatomicalEntity": ["tumor cells", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Step-wise logistic regression (STEPLOG)
The group variable was considered as an ordinal (or binary) dependent variable and the feature vector (multiple marker IBD estimates and covariates) as the independent variables. A nonlinear relationship (logit) between the dependent and independent variables was taken. For binary data (collapsing concordantly affected or unaffected sib pair into one group), a conventional logistic regression was used. For ordinal data, the SAS LOGISTIC [8] procedure fits a parallel lines regression model based on the cumulative distribution probabilities of response categories, rather than on their individual probabilities. The statistical P-value for each (selected) independent variable was obtained from the final model fitting with only selected variables included via an asymptotic chi-squared statistic.
{"AnatomicalEntity": []}