I ran a mixed model regression and obtained the following output. Because I log-transformed the concentration variable, I interpreted the coefficient as follows: the mean concentration is reduced $1.5$ percent each year. The years run from 1993-2010.
Can say also state that the mean concentration is reduced by $26\%$ ($0.01509\cdot 17$) over the $17$ year period? Why or why not?
Why do most people generally state $1$ unit increase in $X$ corresponds to a certain number change in $Y$ rather than infer change over the entire period?
baggerTrend <- lme(Log.Qconc ~ Yearf, random=(~Yearf|MineID), Bagger) Random effects: Formula: ~Yearf | MineID Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr (Intercept) 0.209172851 (Intr) Yearf 0.000374953 -0.478 Residual 0.785367538 Fixed effects: Log.Qconc ~ Year Value Std. Error DF t-value pvalue Intercept 33.71122 6.3901 2762 5.275538 0 Year -0.01509 0.003193 2762 -4.724678 0