sources
– missing persons https://namus.nij.ojp.gov
The National Missing and Unidentified Persons System (NamUs), US Census Bureau 2020 Population Data
– population density https://www.states101.com/populations (2014 population estimates)
– agriculture income https://data.ers.usda.gov/reports.aspx?ID=17839#P9dd070795569412d9525def18d45bde2_4_185iT0R0x0

method for "rural-urban" metric
– population density and agriculture income data values were converted to "standard scores", aka "z-scores": z-score = (data value \[Dash] mean)/SD (see Wikipedia, "Standard score")
– the z-scores were added and divided by 2; result = the 'rural-urban' metric z-score
– note1: 'urban' means "increasing population density"
'rural' means "increasing agriculture income as % of state GDP"
for the 'rural' metric to denote a "rural to urban" value,
the z-scores for agriculture income were 'reversed' by multiplying by "\[Dash]1"
before adding to the population density z-scores
– note2: "NCE" is "normal curve equivalent" (see Wikipedia, "Normal curve equivalent")
tool: Mathematica

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top two plots
Missing persons and 'rural-urban' metrics: note that missing persons t-test indicates that data fluctuations are probably "random" in character.
The large difference of 'rural-urban' means (> 1 SD) for Rep and Dem states indicate that Rep and Dem states are different Sample populations.

the bottom plot
– Missing persons VS 'rural-urban" predictor metric: the r-value of -0.11 indicates that the data is essentially "noise" about the best-fit line.
– Note that purple is used for best-fit line, mean, and SD because the Rep and Dem states data are NOT different Sample populations.