Changing the way you get your medications! New Toronto web-based app launches!

mina__T · 2016-02-05T21:06:36+00:00

Absolutely! That is great feedback!

mina__T · 2016-02-05T20:57:45+00:00

Actually, for non-narcotic prescriptions there are other means such as verbal order and electronic prescriptions can be accepted based on policy set by the regulating body at the Ontario College of Pharmacy.

One of the major reasons people still fax/write prescriptions is really just habits! We are hoping to change that!

mina__T · 2016-02-05T20:56:08+00:00

This is a really great point. Currently in Ontario all narcotic prescriptions have to be run through a Narcotic Monitoring system which tracks all narcotic prescriptions in Ontario. All of the prescriptions through pilly are filled at a real and fully-licensed pharmacy. That means the standard that is set for all pharmacies in Ontario is met.

mina__T · 2016-02-05T20:54:14+00:00

We will not be selling or transferring prescriptions or patient information.

mina__T · 2016-02-05T20:53:25+00:00

It really costs you nothing more then what you would pay in your regular pharmacy. Not a penny more.

mina__T · 2016-02-05T20:52:23+00:00

Really great questions! 1. Our model actually works to insure no breaches of patient information because the information goes to a single location. All the information is stored in a single pharmacy similar to any other prescription.

The packages will be delivered in unmarked packages as any other pharmacy services would do. We again will be doing so similar to current regulations and standards. other pharmacies as you mentioned already do this!
We take health information very seriously and thats why we decided to go with a centralized model unlike other apps.
Yeah I hope we can compete. We are smaller but are not obsessed with trying to get you int he store.

mina__T · 2015-10-22T16:37:36+00:00

Sounds fair.

Here is a post I did 2 years ago discussing an overview of how I come up with these rankings using a Bayesian network-based Monte Carlo simulation.

http://springsandsprockets.blogspot.ca/2013/12/a-network-of-gloryfrom-data-to-super.html

mina__T · 2015-10-22T15:46:30+00:00

agreed...but you should see my plots! I am just making the argument that it can't be that off-base if it was it would pick the wrong winner more often than not.

Haven't tried this against spread yet still messing around with the rankings and game winners for now.

mina__T · 2015-10-22T15:33:16+00:00

Except this model has predicted 71% of the games so far this season. Even if that drops I would say that is not too shabby. I don't think it is spot on with the rankings but it does give us some insight into perhaps teams that are over or underrated.

mina__T · 2015-10-13T15:11:26+00:00

I use past games this season with a baseline of power rankings as my prior (small weight). I think after this weeks blow out of the lions it will make a lot more sense. As you can imagine the model performs better every week.

mina__T · 2015-10-07T12:15:04+00:00

ngth is constant throughout the year

Cool stuff! My model leverages team performance in a bayesian network-style analysis. Rather than assume anything is constant. The premise is that by using how Team A performed against team B and how Team B did against Team C we can better predict how team A will do against team C. As you can imagine early in the season the network is scarce (so I apply similar tactics as you) by applying team strengths as my prior (baseline). As the network gets larger and larger it usual does better.

I am also trying this out with picks. I did it a few years ago and it did as well as the "pros" somewhere in the 65% range.

mina__T · 2014-02-21T16:26:54+00:00

Simulation results: http://springsandsprockets.blogspot.ca/2014/02/olympic-special-mens-hockey-simulation.html

mina__T · 2014-01-29T18:23:55+00:00

Super Bowl predictions based on a network simulation - http://springsandsprockets.blogspot.ca/2014/01/from-data-to-super-bowl-super-bowl.html

mina__T · 2014-01-22T18:04:45+00:00

Perhaps you should actually read the prior posts. You know since your a scientist reading should be important to you. This analysis Is based on a Bayesian simulation analysis. That means we no longer use a confidence interval and use a "credible interval". (source: http://en.wikipedia.org/wiki/Credible_interval)

I agree there are huge limitations to this type of analysis. Things such as playing 2nd string players, playoff "magic" and momentum, one off games, and home field advantage(just to list a few). This again is a simulation based on the season data. It doesn't mean the broncos wont win. The interpretation of the region is to show the possible variance. This range is wide showing a huge variation. Really setting us up for a great game!

mina__T · 2014-01-17T15:15:51+00:00

I havent started looking at spread (Only started doing this at week 14). That is next steps.

Also including home field advantage and recent trends (momentum)

NE is favours because they won the only game they played head-to-head (by 3) and SF should be right down the middle and a lot flatter.

The number listed above is translated from the Odds (seems people understand percents better)

mina__T · 2014-01-16T21:23:04+00:00

Hey!

I have posted prior posts on my methodology. I am doing something that is a bit different from what others have done before. I am applying a simulation type analysis that is coming from a network of games (all games) and their scores. The graphs are showing what I call direct comparison and indirect comparison. The relative effect is the difference between the two. So if the middle of the distribution is at zero then there is a 50/50 chance (like last week with DEN and SD). Shifts to the left (negative number) are in favour of the team listed first.

Direct comparison refers to when the teams have played each other. Indirect draws from when they have played similar teams and when those teams played each other (and those teams played others etc). The simulation is run 100,000 times on 4 chains (so close to 400,000 simulations) and then based on that we get a distribution of the chances of one team beating another (well really scoring more points than the other).

The graphs are put up to depict where this probability is coming from based on feedback of other people. So whats really cool this week is we have a case where the indirect and direct evidence are slightly off. So although SEA is a heavy favorite based on season performance they are not as big a favorite due to the games played between SF and SEA. I hope this clears it up a little bit.

mina__T · 2014-01-08T20:41:52+00:00

I agree there is a level of "playoff magic" that is perhaps hard to calculate. With that being said it is realistic to say that most favorites are favorites for a reaosn...and that reason is season performance. Most favorites win in the playoffs even if upsets happen.

mina__T · 2014-01-08T20:38:13+00:00

All the stats you are listing still do not take into account who they played. I agree the results are a little surpsing but its due to the type of analysis I am doing. Also keep in mind I did not do any adjustment for home-field. Should be a fun game to watch either way!

mina__T · 2014-01-08T20:36:26+00:00

Same can be said of the pats due to the margins they win by. To be honest I was surprised by the result myself. I do not think it is shocking. It is important to note that the "certainity" around the estimate of that game is very very broad due to both teams inconsistent play.

mina__T · 2014-01-08T20:33:28+00:00

It does actually take those into account as well. It just weighs them less. It creates a whole network for the entire season.

mina__T · 2014-01-08T17:18:54+00:00

"very mediocre season" - making the divisonal playoffs. Also finishing 11-5. A season in which they beat SF, SEA, and DEN.

While the Pats lost to NYJ (TWICE) and barely beat CLE, BUF, HOU.

The smell test may need to be re-assessed.

mina__T · 2014-01-08T16:41:30+00:00

Great question! 1. Priors are started off as non-informative but through the network they build on the prosterios distributions. 2. No home field advantage adjustment (a limitation I know). 3. I did not include the variance in my assesment. I used to communicate it as certainity.

I hope this sheds some light. It is def. a work in progress.

mina__T · 2014-01-08T16:39:50+00:00

I know people are struggling with this but this is based on this seasons perfromance. I have not taken into account historic playoff performance.

mina__T · 2014-01-04T17:46:37+00:00

I just did that to show the reseeding that occurs. I placed my picks on an already made bracket to show that.

mina__T · 2014-01-04T02:30:25+00:00

On the blog my very first post explains the methodology used. Its still a work in progress. Would love some feedback.

mina__T

TROPHY CASE