TRIM 3.61 : TRend analysis and Indices for Monitoring data STATISTICS NETHERLANDS Date/Time: 4-7-2016 15:06:11 Title : skylark-1a Comment: Example 1; without overdispersion or autocorrelation" The following 5 variables have been read from file: F:\TRIM\TRIM_manual_demo\skylark.dat 1. Site number of values: 55 2. Time number of values: 8 3. Count missing = 999 4. HABITAT number of values: 2 5. COV2 number of values: 4 Number of sites without positive counts (removed) 0 Number of observed zero counts 0 Number of observed positive counts 202 Total number of observed counts 202 Number of missing counts 238 Total number of counts 440 Total count 2536.0 Sites containing more than 10% of the total count Site Number Observed Total % 3 431.0 17.0 37 266.0 10.5 40 624.0 24.6 Time Point Averages TimePoint Observations Average Index 1 25 8.52 1.00 2 20 8.10 0.95 3 30 10.90 1.28 4 30 11.27 1.32 5 28 12.75 1.50 6 29 14.66 1.72 7 22 17.00 2.00 8 18 18.89 2.22 RESULTS FOR MODEL: Effects for Each Time Point ---------------------------------------------- ESTIMATION METHOD = Maximum Likelihood Total time used: 5.08 seconds GOODNESS OF FIT Chi-square 188.14, df 140, p 0.0041 Likelihood Ratio 184.98, df 140, p 0.0065 AIC (up to a constant) -95.02 WALD-TEST FOR SIGNIFICANCE OF DEVIATIONS FROM LINEAR TREND Wald-Test 20.29, df 6, p 0.0025 PARAMETER ESTIMATES Parameters for Each Time Point Time Additive std.err. Multiplicative std.err. 1 0 1 2 -0.3430 0.1086 0.7096 0.0771 3 -0.1732 0.0927 0.8410 0.0780 4 -0.1875 0.0932 0.8290 0.0773 5 -0.0853 0.0915 0.9182 0.0840 6 0.0213 0.0902 1.0216 0.0922 7 0.0953 0.0924 1.1000 0.1016 8 0.1712 0.0940 1.1867 0.1115 Linear Trend + Deviations for Each Time Additive std.err. Multiplicative std.err. Slope 0.0485 0.0107 1.0497 0.0112 Time Deviations 1 0.2325 0.0539 1.2617 0.0680 2 -0.1591 0.0670 0.8529 0.0571 3 -0.0378 0.0541 0.9629 0.0521 4 -0.1006 0.0539 0.9043 0.0488 5 -0.0469 0.0505 0.9542 0.0481 6 0.0112 0.0466 1.0113 0.0472 7 0.0366 0.0453 1.0373 0.0470 8 0.0640 0.0437 1.0661 0.0466 Time INDICES Time Model std.err. Imputed std.err. 1 1 1 2 0.7096 0.0771 0.7096 0.0771 3 0.8410 0.0780 0.8410 0.0780 4 0.8290 0.0773 0.8290 0.0773 5 0.9182 0.0840 0.9182 0.0840 6 1.0216 0.0922 1.0216 0.0922 7 1.1000 0.1016 1.1000 0.1016 8 1.1867 0.1115 1.1867 0.1115 TIME TOTALS Time Model std.err. Imputed std.err. 1 511 38 511 38 2 362 31 362 31 3 429 26 429 26 4 423 25 423 25 5 469 27 469 27 6 522 27 522 27 7 562 32 562 32 8 606 36 606 36 OVERALL SLOPE MODEL: Moderate increase (p<0.01) ** Additive std.err. Multiplicative std.err. 0.0485 0.0107 1.0497 0.0112 OVERALL SLOPE IMPUTED+(recommended): Moderate increase (p<0.01) ** Additive std.err. Multiplicative std.err. 0.0485 0.0107 1.0497 0.0112