A-1 Monthly Public Assistance Statistical Report Family Investment Program, November 2008

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, December 2008

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2009

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Regional variations in ABC transporter expression along the mouse intestinal tract.

The ATP-binding cassette (ABC) family of proteins comprise a group of membrane transporters involved in the transport of a wide variety of compounds, such as xenobiotics, vitamins, lipids, amino acids, and carbohydrates. Determining their regional expression patterns along the intestinal tract will further characterize their transport functions in the gut. The mRNA expression levels of murine ABC transporters in the duodenum, jejunum, ileum, and colon were examined using the Affymetrix MuU74v2 GeneChip set. Eight ABC transporters (Abcb2, Abcb3, Abcb9, Abcc3, Abcc6, Abcd1, Abcg5, and Abcg8) displayed significant differential gene expression along the intestinal tract, as determined by two statistical models (a global error assessment model and a classic ANOVA, both with a P < 0.01). Concordance with semiquantitative real-time PCR was high. Analyzing the promoters of the differentially expressed ABC transporters did not identify common transcriptional motifs between family members or with other genes; however, the expression profile for Abcb9 was highly correlated with fibulin-1, and both genes share a common complex promoter model involving the NFkappaB, zinc binding protein factor (ZBPF), GC-box factors SP1/GC (SP1F), and early growth response factor (EGRF) transcription binding motifs. The cellular location of another of the differentially expressed ABC transporters, Abcc3, was examined by immunohistochemistry. Staining revealed that the protein is consistently expressed in the basolateral compartment of enterocytes along the anterior-posterior axis of the intestine. Furthermore, the intensity of the staining pattern is concordant with the expression profile. This agrees with previous findings in which the mRNA, protein, and transport function of Abcc3 were increased in the rat distal intestine. These data reveal regional differences in gene expression profiles along the intestinal tract and demonstrate that a complete understanding of intestinal ABC transporter function can only be achieved by examining the physiologically distinct regions of the gut.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2009

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

Iowa Sales and Use Tax Annual Statistical Report 2008

Iowa Sales and Use Tax Annual Statistical Report 2008

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

A-1 Monthly Public Assistance Statistical Report Family Investment Program, November 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, October 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, September 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, August 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, July 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, June 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program

A-1 Monthly Public Assistance Statistical Report Family Investment Program, May 2001

A-1 - Monthly Public Assistance Statistical Report Family Investment Program