In a 2011 study, Smart et al. (2011) collected information on 464 Irish and British patients suffering from low back pain regarding:
the type of low back pain (classified into "nociceptive", "peripheral neuropathic", and "central neuropathic")
the presence/absence of 38 clinical criteria and symptoms relating to low back pain.
Fop et al. (2017) conducted Latent Class Analysis on this data set to retrieve the experts' classifications; and by comparing nested models they were able to select 11 out of 38 criteria which contain the most of the relevant grouping information while avoiding redundancy.
data('lowbackpain')A list containing:
A 464x11 binary matrix indicating the presence/absence of the 11 selected criteria for each of the 464 patients. Rownames are study IDs.
A vector of length 464 indicating the diagnosis each patient received, numerically coded (order has no meaning). The names of the vector give the diagnosis in words.
The index to the criteria explaining which symptom they refer to.
Supplemental Content for Fop et al. (2017): doi:10.1214/17-AOAS1061SUPP
Fop, M, Smart, K, Murphy, TB (2017). Variable Selection for Latent Class Analysis with Application to Low Back Pain Diagnosis. The Annals of Applied Statitics. 11(4), 2080-2110. doi:10.1214/17-aoas1061
Smart, K, Blake, C, Staines, A, Doody, C (2011). The Discriminative Validity of "Nociceptive", "Peripheral Neuropathic", and "Central Sensitization" as Mechanisms-Based Classifications of Musculoskeletal Pain. The Clinical Journal of Pain. 27, 655-663. doi:10.1097/AJP.0b013e318215f16a