How did you model them (aka via polynomial terms interactions or transformations)?

A university medical center urology group was interested in the asso Show more Data Description and Background A university medical center urology group was interested in the association between prostate specific antigen (PSA) and a number of prognostic clinical measurements in men with advanced prostate cancer. Data were collected on 97 men who were about to undergo radical prostectomies. Each line of data set provides information on 8 other variables for each person. Variable Name Variable Description Information cavol Cancer Volume Estimate of prostate cancer volume (cc) weight Weight Prostate weight (gm) age Age Age of patient (years) bph Benign Prostatic Hyperplasia Amount of benign prostatic hyperplasia (cm2) hyperplasia svi Seminal Vesicle Invasion Presence or absence of seminal vesicle invasion: 1 if yes; 0 if no cp Capsular Penetration Degree of capsular penetration (cm) gleason Gleason Score Pathologically determined grade of disease (678). Note a higher Gleason score indicates worse prognosis. psa PSA Level Serum prostate-specific antigen level (mg/ml) PSA is commonly used as a screening mechanism for detecting prostate cancer. However to be an efficient screening tool it is important that we understand how PSA levels relate to factors that may determine prognosis and outcome. The PSA test measures the blood level of prostate-specific antigen an enzyme produced by the prostate. PSA levels under 4 ng/mL (nanograms per milliliter) are generally considered normal while levels over 4 ng/mL are considered abnormal (although in men over 65 levels up to 6.5 ng/mL may be acceptable depending upon each laboratorys reference ranges). PSA levels between 4 and 10 ng/mL indicate a risk of prostate cancer higher than normal but the risk does not seem to rise within this six-point range. When the PSA level is above 10 ng/mL the association with cancer becomes stronger. However PSA is not a perfect test. Some men with prostate cancer do not have an elevated PSA and most men with an elevated PSA do not have prostate cancer. PSA levels can change for many reasons other than cancer. Two common causes of high PSA levels are enlargement of the prostate (benign prostatic hypertrophy (BPH)) and infection in the prostate (prostatitis). Some of the variable names may look unfamiliar to you please use resources on the web if you feel unsure as to what these variables measure. The section above is based on excerpts from Wikipedia.org and you can also find variable definitions at http://www.prostate-cancer.org/resource/glossary.html. For example a large tumor may invade surrounding tissue and penetrate the wall of the prostate (variable svi and cp). Also benign hyperplasia is associated with higher PSA levels but is non-cancerous (variable bph). The goal of the analysis is to develop a model for PSA to be used for inferential purposes. Your model should be parsimonious that is a model that balances both explanatory power with simplicity. To this end you may employ any of the methods learned in class. Write up a report (5-7 pages) describing how you obtained this model. Below is a list of things to address in the report. Are all the assumptions needed to fit the model satisfied? Do any transformations need to be applied to the response and/or explanatory variables in order to correct for any model deviations? Are there any outliers in the dataset? Are they adversely affecting the estimates obtained using the least squares method? Recall that the goal of model building is not to build the model that best fits your particular dataset but rather a model that can generalize. Consequently what is the method you will employ to select a model? How many variables will you use? How did you model them (aka via polynomial terms interactions or transformations)? Show less

Place this order or similar order and get an amazing discount. USE Discount code “GET20” for 20% discount