Plotting three-piece regression lines in r

0
votes

I have a three-piece regression model that I’m trying to plot. The regression parameters are here:

qdata=data.frame(breakpoint1=1.092201, breakpoint2=6.153361, slope1=1707, 
slope2=114.6, slope3=-12.09, intercept1=176.6, intercept2=1916, 
intercept3=2696)

And the data are here:

f=structure(list(weight = c(122, 306, 1040, 1498, 1980, 1980, 1983, 
2060, 2110, 2180, 2180, 2192.5, 2200, 2219.5, 2230, 2256.5, 2260, 
2290, 2300, 2350, 2361, 2370, 2380, 2615, 2724, 1952, 1993, 2029.5, 
2088, 2106, 2100, 2100, 2100, 2160, 2170, 2170, 2180, 2180, 2180, 
2200, 2220, 2220, 2220, 2220, 2220, 2230, 2230, 2240, 2260, 2270, 
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1544L, 1545L, 1546L, 1547L, 1548L, 1550L, 1551L, 1552L, 1553L, 
1554L, 1555L, 1556L, 1557L, 1558L, 1559L, 1560L, 1561L, 1562L, 
1563L, 1564L, 1565L, 1566L, 1567L, 1568L, 1569L, 1570L, 1571L, 
1572L, 1574L, 1575L, 1576L, 1577L, 1578L, 1579L, 1580L, 1779L, 
1780L, 1781L, 1782L, 1783L, 1784L, 1785L, 1786L, 1787L, 1788L, 
1789L, 1790L, 1791L, 1792L, 1793L, 1794L, 1795L, 1796L, 1797L, 
2058L, 2059L, 2060L, 2061L, 2062L, 2063L, 2064L, 2065L, 2066L, 
2067L, 2068L, 2069L, 2070L, 2071L, 2072L, 2073L, 2074L, 2075L, 
2076L, 2077L, 2078L, 2079L, 2080L, 2081L, 2082L, 2083L, 2084L, 
2085L, 2086L, 2087L, 2088L, 2089L, 2090L, 2091L, 2092L, 2093L, 
2094L, 2095L, 2096L, 2097L, 2098L, 2099L, 2100L, 2101L, 2102L, 
2103L, 2104L, 2105L))

And I can plot the three lines using this code:

plot(f$age,f$weight)
curve(qdata$intercept1 + qdata$slope1*x, add=T, from=0, to=qdata$breakpoint1, col=2)
curve(qdata$intercept2 + qdata$slope2*x, add=T, from=qdata$breakpoint1, to=qdata$breakpoint2, col=2)
curve(qdata$intercept3 + qdata$slope3*x, add=T, from=qdata$breakpoint2, to=max(f$age), col=2)

For my purposes, the slope of the third segment is not biologically significant, so for presenting the data, I would like to set the slope of the third segment to zero:

plot(f$age,f$weight)
curve(qdata$intercept1 + qdata$slope1*x, add=T, from=0, to=qdata$breakpoint1, col=2)
curve(qdata$intercept2 + qdata$slope2*x, add=T, from=qdata$breakpoint1, to=qdata$breakpoint2, col=2)
curve(qdata$intercept3 + 0*x, add=T, from=qdata$intecept3, to=max(f$age), col=2)

However, when I do that, I get a gap between the end of the second segment line and the beginning of the third. I’m wondering if anyone knows how to keep the second and third lines connected while setting the slope of the third line to zero.

1
rplotregression
Your example isn't reproducible because we don't have f. – joran
...the slope of the third segment is not biologically significant, so for presenting the data, I would like to set the slope of the third segment to zero Obviously I don't know the specifics of your problem, but this raises a huge red flag for me. If the data are not statistically significant, you should display the true trendline with some sort of visualization of error or confidence so your audience can tell that the data aren't significant. If they are statistically significant, perhaps you should question your assumption that they are not biologically significant. – Joe
@Joe: thanks, that's definitely something to consider. The third slope is not statistically significant, and showing the error would be a good idea. For the particular question I'm asking, I'm not really discussing the third segment - I'd really like to highlight the trends of the first and second segments without making the third segment too distracting, which is why I'm still interested in knowing how to display it with the slope set to zero, in which case I would still verbally report the details of the third segment int he paper. – Erica
Thanks for adding your data; I've now been able to provide a technical solution to your problem. However, especially after seeing your data, I would still discourage you from making this change. Looking at the original graph, the 'flatness' of that trendline is obvious to me, and you can make it even more so by adding an error region. You can highlight the initial growth by coloring that portion of the graph or even truncating it. However, changing your data or its visualization to fit an idealized picture is never a good idea, even if the change is very minor. – Joe

1 Answers

0
votes

You have two problems with the code as provided. To get the trendline to start in the correct place on the x-axis you simply must fix what I assume was a typo in your code:

curve(qdata$intercept3 + 0*x, add=T, from=qdata$intecept3, to=max(f$age), col=2)

should be written as:

curve(qdata$intercept3 + 0*x, add=T, from=qdata$breakpoint2, to=max(f$age), col=2)

The reason for the discontinuity on the y-axis is slightly more complicated but still easy to fix. The original line connected perfectly with the end of the second line because it began at the y-intercept and trended downward slightly. When you reset the slope to 0, the new line was projected above the desired point. Therefore, to draw the line as desired, you will need to re-calculate the y intercept that will produce a flat line passing through the end of the second trendline:

qdata$fake.intercept <- qdata$intercept2 + qdata$slope2 * qdata$breakpoint2
curve(qdata$fake.intercept + 0 * x, add = T, from = qdata$breakpoint2, to = max(f$age), col = 2)

This should produce the following graph, which I believe is what you want: enter image description here