New features mentioned in SAS Tech Report, May 2013

New features mentioned in SAS Tech Report, May 2013

I haven't use SAS for my projects for a while. Today I read the SAS Tech Report in my emailbox. The Graphics focus area has been updated and is a great place to learn some new features/PROC SGPLOT. SAS is working hard on making better graphics.

Chris Daman has posted a few blogs about multilevel analysis:

• Multilevel Models Part 1: Do I Need a Multilevel Model?
• Multilevel Models Part 2: What is a Multilevel Model?
• When is a Multilevel Model not appropriate?

Does 3 minutes of exercise and two fasts a week (5:2) work?

Does 3 minutes of exercise and two fasts a week (5:2) and others
 
A few weeks ago, I watched a presention on PBS channel by Dr. Michael Mosley about he dealed with his high blood glucose (diabetes). He amazingly found 3 minutes of exercise and two fasts a week works for him.

• This new diet mimics fasting by “rebooting” the body - State Column (2015)
• Reaping The Health Benefits Of Fasting Without Actually Fasting - Forbes (2015)
• Brandhorst (2015). A Periodic Diet that Mimics Fasting Promotes Multi-System Regeneration, Enhanced Cognitive Performance, and Healthspan
• 'FastDiet' book is attracting dieters, and doubters - USA Today
• 'The Fast Diet': Recipes for Low-Calorie Meals - ABCNews
• Michael Mosley: 'The Fast Diet' Author On Self-Experimentation, Fasting And Coming To America - Huffington Post
• 3 Minutes of Exercise and Two Fasts a Week: Is This the Future of Fitness?
• Feast and Famine: Controversial 'Fast Diet' Weight Loss Plan Is Eat for 5 Days, Fast for 2 - ABCNews
• The fast diet - Michael Mosley

Grant (2017). Running on empty (TheScientist)


Francesco (2018): A time to fast, Ludwig (2018): Dietary fat: From foe to friend?

The ancient civilization also practiced this similar activity (fasting) for good health and longevity long times ago: some are simple, some are much more complicated, called 'Inedia' and Chinese called this '辟谷' (Pi Gu). Dr. Michael Mosley did a great job on promoting this activity, and he makes this more practiable.

• Howard (2017). Does fasting on alternate days work? A new study weighs in

• 拨开迷雾看辟谷养生

Integrated Health Interview Series

Integrated Health Interview Series (IHIS)

If you're working on trend projects using US National Health Interview Survey. IHIS, a database of NHIS data that facilitates trend analyses, can be a big helper. This well-organized online documents included NHIS annual data from the 1960s to the present. You can easily linked to additional variables in NHIS public use data and comprehensive on-line documentation.

Medicare Provider Charge Data

Medicare Provider Charge Data

Source: Centers for Medicare & Medicaid Services

 

"As part of the Obama administration's work to make our health care system more affordable and accountable, data are being released that show significant variation across the country and within communities in what hospitals charge for common inpatient services.

 

The data provided here include hospital-specific charges for the more than 3,000 U.S. hospitals that receive Medicare Inpatient Prospective Payment System (IPPS) payments for the top 100 most frequently billed discharges, paid under Medicare based on a rate per discharge using the Medicare Severity Diagnosis Related Group (MS-DRG) for Fiscal Year (FY) 2011. These DRGs represent almost 7 million discharges or 60 percent of total Medicare IPPS discharges.

 

Hospitals determine what they will charge for items and services provided to patients and these charges are the amount the hospital bills for an item or service. The Total Payment amount includes the MS-DRG amount, bill total per diem, beneficiary primary payer claim payment amount, beneficiary Part A coinsurance amount, beneficiary deductible amount, beneficiary blood deducible amount and DRG outlier amount.

 

For these DRGs, average charges and average Medicare payments are calculated at the individual hospital level. Users will be able to make comparisons between the amount charged by individual hospitals within local markets, and nationwide, for services that might be furnished in connection with a particular inpatient stay.

 

Data are being made available in Microsoft Excel (.xlsx) format and comma separated values (.csv) format."

 

Inpatient Charge Data, FY2011, Microsoft Excel version 

Inpatient Charge Data, FY2011, Comma Separated Values (CSV) version 

 

Hospital Prices No Longer Secret As New Data Reveals Bewildering System, Staggering Cost Differences - 05/08/2013 The Huffington Post

Free PDF Related Utilities

Free PDF Related Utilities

• Briss, an open-source application, is an excellent handyware for cropping/trimming PDF pages. It groups all the different page sizes in your document together and will require the user to make cropping decisions for each group of pages that is of a similar size. It provides the option to exclude certain pages or page ranges from the cropping action. It crops PDFs with simple GUI; it can crop different regions into separate pages, and multi column/pages. It's very handy.
• ORPALIS PDF Reducer Free is a freeware version of PDF compression Software to help get existing PDF files reduced up to 80% more than concurrent products.
• FileOptimizer is an another one for file size optimizer. It supports a lot of file types from audio/video (MP3, OGG, OGV), image (GIF, JPEG, PNG), and even office formats (DOCX, XLSX, ODT, PDF) and system files (DLL, EXE). By default, FileOptimizer will remove additional metadata, and other unneeded information, but will keep original files in your recycle bin. Notes: It might corrupt some of them especially EXE files.
• PdfSam is a free open source tool to split and merge pdf documents (it keeps bookmarks of original pdf files).
• PDFTK Builder and GUI for PDFTK are free graphical interfaces to the Windows version of pdftk making it much easier to use. pdftk is an electronic staple-remover, hole-punch, binder, secret-decoder-ring, and X-Ray-glasses. Pdftk is a simple tool for doing everyday things with PDF documents.
• Foxit Reader is the high volume PDF reader providing a complete PDF creation solution, providing the power of PDF creation to every desktop. Foxit Reader Version 6 has a lot of improvement. I use PDF-XChange as an portable Apps, but I am thinking to use Foxit Reader more.
• PDF-XChange Viewer presents users with an alternative to Adobe's Acrobat Reader. It gives users more options such as typewriter than its competition, allowing for more in-depth markups.
• STDU Viewer is a free viewer for multiple file formats including TIFF, PDF, DjVu, XPS, JBIG2, and WWF format. Starting from 1.6.86, STDU Viewer supports MOBI/AZW and FB2 formats and from 1.6.151, It supports EPub format. You can use STDV Viewer to print the files of these formats. STDV Viewer is getting better and better.
• SumatraPDF is a PDF, EPUB, MOBI, CHM, XPS, DjVu, CBZ and CBR reader for Windows. It's small and starts up fast.
• PDFill PDF Tools are FREE PDF functions to merge, split, reorder, delete, encrypt, decrypt, rotate, crop and reformat PDF (change margin size) pages,  to add information, header, footer and watermark, to convert images to PDF, PDF to images or PostScript to PDF, to delete, flatten and list form fields, to scan to pdf, to create transparent image, and more.
• K2pdfopt optimizes PDF/DJVU files for mobile e-readers (e.g. the Kindle) and smartphones. It works well on multi-column PDF/DJVU files and can re-flow text even on scanned PDF files. K2pdfopt is open source.

The Big, Fat World of Lipids

The Big, Fat World of Lipids

 from Inside Life Science Series by National Institute of General Medical Sciences

"When you have your cholesterol checked, the doctor typically provides your levels of three fats found in the blood: LDL, HDL and triglycerides. But did you know your body contains thousands of other types of fats, or lipids? "

"In human plasma alone, researchers have identified some 600 different types relevant to our health. Many lipids are also associated with diseases-diabetes, stroke, cancer, arthritis, Alzheimer's disease, to name a few. Learning more about them could point to new ways to diagnose and treat lipid-related conditions."... more

[Notes: Inside Life Science is part of Science Education, which include a lot of topic in layman laungage with nice graphs.]

Self-Medication in Animals

Self-Medication in Animals

A entertaining article from Science about how animals find the meds for themselves. It reminds me when we are using the evidences from clinic trials as the best source (?). Please don't forget the other types of studies.

"Finally, the study of animal medication will have direct relevance for human food production and health. Disease problems in agricultural organisms can worsen when humans interfere with the ability of animals to medicate. For example, increases in parasitism and disease in honeybees can be linked to selection by beekeepers for reduced resin deposition by their bees. A re-introduction of such behavior in managed bees would likely have great benefits for disease management. In addition, as self-medicating animals, humans still derive many of their medicines from natural products, and plants remain the most promising source of future drugs. Studies of animal medication may lead the way in discovering new drugs to relieve human suffering. "

Full text

Stata Tips - Stata Journal

Stata Tips of The Stata Journal etc.

Blog: Resources and Other Tips

Blog: Speaking Stata of the Stata Journal

Blog: Stata News: In the spotlight

Stata FAQs

Stata Blogs

The Tips from Stata Journal: 

• 140: Shorter or fewer category labels with graph bar [21(1)]
• 139: The by() option of graph can work better than graph combine
• 138: Local macros have local scope
• 137: Interpreting constraints on slopes of rank-deficient design matrices
• 136: Between-group comparisons in a scatterplot with weighted markers
• 135: Leaps and bounds
• 134: Multiplicative and marginal interaction effects in nonlinear models
• 133: Box plots that show median and quartiles only
• 131: Custom legends for graphs that use translucency
• Tips for calculating and displaying risk-standardized hospital outcomes in Stata
• 130: 106610 and all that: Date variables that need to be fixed
• 129: Efficiently processing textual data with Stata's new Unicode features
• 128: Marginal effects in log-transformed models: A trade application
• 127: Use capture noisily groups
• 126: Handling irregularly spaced high-frequency transactions data
• 125: Binned residual plots for assessing the fit of regression models for binary outcomes
• 124: Passing temporary variables to subprograms
• 123: Spell boundaries
• 122: Variable bar widths in two-way graphs
• 121: Box plots side by side
• 120: Certifying subroutines
• 119: Expanding datasets for graphical ends
• 118: Orthogonalizing powered and product terms using residual centering
• 117: graph combine–Combining graphs
• 116: Where did my p-values go? (Part 3)
• 115: How to properly estimate the multinomial probit model with heteroskedastic errors
• 114: Expand paired dates to pairs of dates
• 113: Changing a variable's format: What it does and does not mean
• 112: Where did my p-values go? (Part 2)
• 111: More on working with weeks (erratum)
• 110: How to get the optimal k-means cluster solution
• 109: How to combine variables with missing values
• 108: On adding and constraining
• 107: The baseline is now reported
• 106: With or without reference
• 105: Daily dates with missing days
• 104: Added text and title options
• 103: Expressing confidence with gradations
• 102: Highlighting specific bars
• 101: Previous but different
• 100: Mata and the case of the missing macros
• 99: Taking extra care with encode
• 98: Counting substrings within strings
• 97: Getting at ρ's and σ's
• 96: Cube roots
• 95: Estimation of error covariances in a linear model
• 94: Manipulation of prediction parameters for parametric survival regression models
• 93: Handling multiple y axes on twoway graphs 
• 92: Manual implementation of permutations and bootstraps
• 91: Putting unabbreviated varlists into local macros
• 90: Displaying partial results
• 89: Estimating means and percentiles following multiple imputation
• 88: Efficiently evaluating elasticities with the margins command
• 87: Interpretation of interactions in nonlinear models
• 86: The missing() function
• 85: Looping over nonintegers
• 84: Summing missings
• 83: Merging multilingual datasets
• 82: Grounds for grids on graphs
• 81: A table of graphs
• 80: Constructing a group variable with specified group sizes
• 79: Optional arguments to options
• 78: Going gray gracefully: Highlighting subsets and downplaying substrates
• 77: (Re)using macros in multiple do-files
• 76: Separating seasonal time series
• Evaluating concavity for production and cost functions
• 75: Setting up Stata for a presentation
• 74: firstonly, a new option for tab2
• 73: append with care!
• 72: Using the Graph Recorder to create a pseudograph scheme commands
• 71: The problem of split identity, or how to group dyads
• 70: Beware the evaluating equal sign
• 69: Producing log files based on successful interactive
• 68: Week assumptions
• 67: J() now has greater replicating powers
• 66: ds—A hidden gem
• 65: Beware the backstabbing backslash
• 64: Cleaning up user-entered string variables
• 63: Modeling proportions
• 62: Plotting on reversed scales
• 61: Decimal commas in results output and data input
• 60: Making fast and easy changes to files with filefilter
• 59: Plotting on any transformed scale
• 58: nl is not just for nonlinear models
• 57: How to reinstall Stata
• 56: Writing parameterized text files
• 55: Better axis labeling for time points and time intervals
• 54: Post your results
• 53: Where did my p–values go?
• 52: Generating composite categorical variables
• 51: Events in intervals
• 50: Efficient use of summarize
• 49: Range frame plots
• 48: Discrete uses for uniform()
• 47: Quantile–quantile plots without programming
• 46: Step we gaily, on we go
• 45: Getting those data into shape
• 44: Get a handle on your sample
• 43: Remainders, selections, sequences, extractions: Uses of the modulus
• 42: The overlay problem: Offset for clarity
• 41: Monitoring loop iterations
• 40: Taking care of business
• 39: In a list or out? In a range or out?
• 38: Testing for groupwise heteroskedasticity
• 37: And the last shall be first
• 36: Which observations? Erratum
• 35: Detecting whether data have changed
• 34: Tabulation by listing
• 33: Sweet sixteen: Hexadecimal formats and precision problems
• 32: Do not stop
• 31: Scalar or variable? The problem of ambiguous names
• 30: May the source be with you
• 29: For all times and all places
• 28: Precise control of dataset sort order
• 27: Classifying data points on scatter plots
• 26: Maximizing compatibility between Macintosh and Windows
• 25: Sequence index plots
• 24: Axis labels on two or more levels
• 23: Regaining control over axis ranges
• 22: Variable name abbreviation
• 21: The arrows of outrageous fortune
• 20: Generating histogram bin variables
• 19: A way to leaner, faster graphs
• 16: Using input to generate variables
• 17: Filling in the gaps
• 18: Making keys functional
• 15: Function graphs on the fly
• 14: Using value labels in expressions
• 13: generate and replace use the current sort order
• 12: Tuning the plot region aspect ratio
• 11: The nolog option with maximum–likelihood modeling commands
• 10: Fine control of axis title positions
• 9: Following special sequences
• 8: Splitting time–span records with categorical time–varying covariates
• 7: Copying and pasting under Windows
• 6: Inserting awkward characters in the plot
• 5: Ensuring programs preserve dataset sort order
• 4: Using display as an online calculator
• 3: How to be assertive
• 2: Building with floors and ceilings
• 1: The eform() option of regress  [2003;3(4)]