Covariance structure accounts for the panel design and the four variance components: unit variation, period variation, unit by period interaction variation and index (or residual) variation. The model incorporates unit, period, unit by period, and index variance components. It also includes a provision for unit correlation and period autocorrelation.
cov_panel_dsgn(
paneldsgn = matrix(50, 1, 10),
nrepeats = 1,
unit_var = NULL,
period_var = NULL,
unitperiod_var = NULL,
index_var = NULL,
unit_rho = 1,
period_rho = 0
)A list containing the covariance matrix (cov) for the panel design,
the input panel design (paneldsgn), the input nrepeats design
(nrepeats.dsgn) and the function call.
A matrix (dimensions: number of panels (rows) by number of periods (columns)) containing the number of units visited for each combination of panel and period. Default is matrix(50, 1, 10) which is a single panel of 50 units visited 10 times, typical time is a period.
Either NULL or a list of matrices the same length as
paneldsgn specifying the number of revisits made to units in a panel in the
same period for each design. Specifying NULL indicates that number of
revisits to units is the same for all panels and for all periods and for
all panel designs. The default is NULL, a single visit. Names must match
list names in paneldsgn.
The variance component estimate for unit. The default is
NULL.
The variance component estimate for period The default is
NULL.
The variance component estimate for unit by period
interaction. The default is NULL.
The variance component estimate for index error. The
default is NULL.
Unit correlation across periods. The default is 1.
Period autocorrelation. The default is 0.
Tony Olsen Olsen.Tony@epa.gov
Covariance structure accounts for the panel design and the four variance components: unit variation, period variation, unit by period interaction variation and index (or residual) variation. Uses the model structure defined by Urquhart 2012.
If nrepeats is NULL, then no units sampled more than once in a specific
panel, period combination) and then unit by period and index variances are
added together or user may have only estimated unit, period and unit by
period variance components so that index component is zero. It calculates
the covariance matrix for the simple linear regression. The standard error
for a linear trend coefficient is the square root of the variance.
Urquhart, N. S., W. S. Overton, et al. (1993) Comparing sampling designs for monitoring ecological status and trends: impact of temporal patterns. In: Statistics for the Environment. V. Barnett and K. F. Turkman. John Wiley & Sons, New York, pp. 71-86.
Urquhart, N. S. and T. M. Kincaid (1999). Designs for detecting trends from repeated surveys of ecological resources. Journal of Agricultural, Biological, and Environmental Statistics, 4(4), 404-414.
Urquhart, N. S. (2012). The role of monitoring design in detecting trend in long-term ecological monitoring studies. In: Design and Analysis of Long-term Ecological Monitoring Studies. R. A. Gitzen, J. J. Millspaugh, A. B. Cooper, and D. S. Licht (eds.). Cambridge University Press, New York, pp. 151-173.
power_dsgnfor power calculations of multiple panel designs