I produce multiple quantile regression plots in Stata but I can not add a legend. Could you please advise me how can add a legend for quantile plot?
However, when I run my code I always run into the following error:
grqreg, ci ols olsci || legend(on)
error option legend() not allowed
qreg yield_1 ndre_20 dem_16, quantile(.5)
grqreg, ci ols olsci
enter image description here
Could you please someone advise me how add legend for quantile regression plot
Related
Hello!
After running a model for a simple linear regression model in pymc3, I'm trying to do a plot.
As you can see both plots show the "posterior predictive mean score", but I was wondering whether can I plot this distribution around the "posterior predictive mean score" (not around "observed score"), in arviz, similar to what is shown in the first figure?
Both figures were made using the same data:
Score <- c(78.93,58.2,67.47,37.47,45.65,32.92,29.97)
Drugs <- c(1.17,2.97,3.26,4.69,5.83,6,6.41)
EDIT:
Bayesplot with bounds:
how to estimate linear regression using OLS with stata command 'regress', how to transform the slope of a in order to meet the following regression form
enter image description here
a=E/pib
regress bc a
I think your question seems to be about (1-b2).
After regress bc a, your coefficient is exactly 1-b2, so if you want to get b2, then just subtract it from 1 .
I have this scatter plot:
It's month-number. If I convert month to a number (1-12), I can calculate regression line like this:
Is there anyway to keep the month, not having to convert to number and still run linear regression?
Thanks!
Try leaving your scatter plot with the numbers for the x-axis, but customizing your tick labels to show months.
Add this to your options object.
hAxis:{ticks:[{v:1,f:'Jan'},{v:2,f:'Feb'},{v:3,f:'Mar'},{v:4,f:'Apr'},
{v:5,f:'May'},{v:6,f:'Jun'},{v:7,f:'Jul'},{v:8,f:'Aug'},
{v:9,f:'Sep'},{v:10,f:'Oct'},{v:11,f:'Nov'},{v:12,f:'Dec'}]}
I'm using PROC LOGISTIC procedure in SAS and option SELECTION=SCORE which gives me few logistic regression models and their Chi-Square values. My question would be which model is better - with smaller Chi-Square or bigger?
In general, the larger chi-squared statistic will correspond with a lower p-value (more significance). However, it is important to know the shape of the chi-squared distribution and also the number of degrees of freedom. As you can see in the graph, the relationship between p and chi-squared changes based on the degrees of freedom.
Score for Chi-Square is larger, the model is better.
I am trying to create a single ROC curve for three bio-markers on a common population.
I have already created an overlay curve from proc logistic statement. is there any way in SAS (among default options) to label the specific points on one of the bio-markers.
also, I would like to create a horizontal and vertical lines that depict the Sn and 1-Sp for those specific points.
is there an easier way to do this other than creating a annotation dataset and plotting a graph through proc gplot?
Thanks in advance!!
Among default options, the answer is no. SAS gives you options to control certain aspects of the ROC curves in the roc and rocoptions options in the proc logistic statement, but it doesn't support adding specific features to plots directly within the procedure.
To get the features you're looking for, as you said, you'll need to plot the raw ROC data using a graphics procedure. I like sgplot, the ODS graphics successor to gplot. Assuming you know exactly which points you want to label ahead of time, horizontal and vertical lines for the sensitivity and 1 - specificity can be generated using the refline statement in sgplot.
An annotation dataset may be the best way to go to label specific points. If you're using sgplot, you can generate an SG annotation dataset using the SG annotation macros. More information regarding SG annotation, including the use of the macros, can be found here. The macros are located in the default SAS autocall macro library so they should be able to be referenced without any special fussing. Once you have your dataset, you can feed it into sgplot using the sganno= option in the proc sgplot statement.