Creating graphs with xtline

[Ahmed Ibrahim]

Hello everyone,

I have a data showing the quality of observations before and after a certain ste. (Sample data below)

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(serial_number Quality process_step)
1 0 3
1 3 3
2 2 2
2 0 1
3 1 1
3 3 3
4 1 1
4 2 2
5 0 0
5 0 0
end

i am trying to generate a graph showing the general trend in change in quality (I've attached a sample here)



i tried using xtline with the following code

  
 xtline Quality , ///
        overlay ///
        xsc(r(0.95 2.05) ) ///
        xlabel(1 2, valuelabel labsize(small)) ylabel(, valuelabel labsize(small) ) ///
        i(serial_number) t(process_step) ///
        legend(off)

but the graph that is generated makes it look like there are only 6 observations - is there a way to somehow "jitter" the lines to somehow show the number of lines that are overlaid?

Thanks in advance

regards
Ahmed

[Nick Cox]

What plays the role of time in your example?

[Ahmed Ibrahim]

Hi Nick,

I'm not sure if you mean in my data or the figure I provided as an example here

In my data, i am using the process_step variable - 1 for before and 2 for after processing.

I also realize the sample data I provided is wrong. The following is the correct sample data.

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(serial_number Quality process_step )
 1 0 2
 1 3 1
 2 2 1
 2 0 2
 3 1 2
 3 3 1
 4 1 2
 4 2 1
 5 0 1
 5 0 2
 end

I'm also open to using any other program if there is one better suited for this task.

[Nick Cox]

The answer is presumably process_step so that

xtset serial_number process_step

was what enabled xtline.

Judging by your data example your data are only barely like those in the display. You have a counted or categorical scale with only a few distinct values, and line plots just result in over-plotting. So, one answer is to turn this into a transition matrix or contingency table.

I used tabplot from the Stata Journal, written up systematically in SJ 16(2), latest version of files in 20(3) but example closer to this in 12(3).

SJ-20-3 gr0066_2 . . . . . . . . . . . . . . . . Software update for tabplot
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q3/20 SJ 20(3):757--758
added new options frame() and frameopts() allowing framing
of bars and so-called thermometer plots or charts

SJ-17-3 gr0066_1 . . . . . . . . . . . . . . . . Software update for tabplot
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q3/17 SJ 17(3):779
added options for reversing axis scales; improved handling of
axis labels containing quotation marks

SJ-16-2 gr0066 . . . . . . Speaking Stata: Multiple bar charts in table form
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q2/16 SJ 16(2):491--510
provides multiple bar charts in table form representing
contingency tables for one, two, or three categorical variables

SJ-12-3 gr0053 . Speaking Stata: Axis practice, or what goes where on a graph
(help multqplot if installed) . . . . . . . . . . . . . . . N. J. Cox
Q3/12 SJ 12(3):549--561
discusses variations on what goes on each axis of a two-way
plot; provides multiple quantile plots

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(serial_number Quality process_step )
 1 0 2
 1 3 1
 2 2 1
 2 0 2
 3 1 2
 3 3 1
 4 1 2
 4 2 1
 5 0 1
 5 0 2
 end
 
 reshape wide Quality, i(serial) j(process_step)
 
 set scheme s1color 
 tabplot Quality2 Quality1, showval yasis xasis

The example graph is not very interesting, but the version for your full dataset may be better.

[Ahmed Ibrahim]

a

[Ahmed Ibrahim]

The answer is presumably process_step so that

xtset serial_number process_step

was what enabled xtline.

Judging by your data example your data are only barely like those in the display. You have a counted or categorical scale with only a few distinct values, and line plots just result in over-plotting. So, one answer is to turn this into a transition matrix or contingency table.

I used tabplot from the Stata Journal, written up systematically in SJ 16(2), latest version of files in 20(3) but example closer to this in 12(3).

SJ-20-3 gr0066_2 . . . . . . . . . . . . . . . . Software update for tabplot
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q3/20 SJ 20(3):757--758
added new options frame() and frameopts() allowing framing
of bars and so-called thermometer plots or charts

SJ-17-3 gr0066_1 . . . . . . . . . . . . . . . . Software update for tabplot
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q3/17 SJ 17(3):779
added options for reversing axis scales; improved handling of
axis labels containing quotation marks

SJ-16-2 gr0066 . . . . . . Speaking Stata: Multiple bar charts in table form
(help tabplot if installed) . . . . . . . . . . . . . . . . N. J. Cox
Q2/16 SJ 16(2):491--510
provides multiple bar charts in table form representing
contingency tables for one, two, or three categorical variables

SJ-12-3 gr0053 . Speaking Stata: Axis practice, or what goes where on a graph
(help multqplot if installed) . . . . . . . . . . . . . . . N. J. Cox
Q3/12 SJ 12(3):549--561
discusses variations on what goes on each axis of a two-way
plot; provides multiple quantile plots

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(serial_number Quality process_step )
1 0 2
1 3 1
2 2 1
2 0 2
3 1 2
3 3 1
4 1 2
4 2 1
5 0 1
5 0 2
end

reshape wide Quality, i(serial) j(process_step)

set scheme s1color
tabplot Quality2 Quality1, showval yasis xasis

The example graph is not very interesting, but the version for your full dataset may be better.


[ATTACH=CONFIG]n1607707[/ATTACH]

Thank you Nick. This was helpful.

I did some research and also found another way to go about this. See code below.

    reshape wide Quality, i(serial_number) j(Motioncorrectedornot)
    
    *generate new quality variables
        gen recode_quality1=Quality1
        gen recode_quality2=Quality2
        
    *count
        count if Quality1==Quality2
        
        count if Quality1<Quality2
        
        count if Quality1>Quality2
        

    *create loop to add small amount to new quality
        local add_to=0.01
        
        forval i=1/38 {
            
            replace recode_quality1 = recode_quality1 + `add_to' if serial_number==`i'
            
            local add_to = `add_to' + 0.01
        }
        
        gen diff=recode_quality1-recode_quality2
            sum diff, detail
            
        tab recode_quality1
        
        
    *drop old variables
        drop Quality1 Quality2
        
    *reshape back
        reshape long recode_quality, i(serial_number) j(Motioncorrectedornot)
        
    xtline recode_quality , ///
        overlay ///
        xtitle("") ytitle("Motion") ///
        xsc(r(0.95 2.05) ) ///
        ylabel(0.25 "None" ///
               1.25 "Some" ///
               2.25 "Moderate" ///
               3.25 "Severe" ///
               , labsize(small)) ///
        xlabel(1 2, valuelabel labsize(small) ) ///
        i(serial_number) t(Motioncorrectedornot) ///
        legend(off) ///
        name(trendline, replace)
            graph export "./Graphs/trendline.tif", replace