I know in my experience "Cond" (conductivity??) doesn't vary much within a stream except for during high flow events, and I would imagine the same is true for TDS. If these are all low flow values, you could possibly determine a mean/median value to use for the missing data points. Obviously this is going to be different if you are sampling storm events. If you have stage data and lots of data points, you may be able to model the parameters as a function of stage. HTH
Rich Shepard wrote: > > Because of regulatory requirement changes over several decades and weather > conditions preventing site access the variables in my data set have > different lengths. I'd like guidance on how to perform linear regressions > and other models with these variables. > > For example, there are 2206 rows for the parameter "TDS" but only 1191 > rows for the parameter "Cond." Such discrepancies are common in these > data. > > Is there a reference I can read to learn how to analyze such data? > > Rich > > ______________________________________________ > R-help@ mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- View this message in context: http://r.789695.n4.nabble.com/Working-With-Variables-Having-Different-Lengths-tp3926023p3926158.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
