Hi!

I have been trying to regress a random effect model, using SAS and have bumped into quite some probs. For some reason, my output displays a standard deviation of 0 for my covariance matrices. Please find below a specification of my model and my output. My random variable is "bedrijf"(=company) Can somebody please explain why my covariances do not display a Z-statistic? Thanks in advance!!!

1. My model
proc mixed covtest;
class Bedrijf weekdays ;
Model corwin= weekdays Period1 Period2 Period3 Stir EMP__pos_index_return EMP__neg_index_return Ltir Volatility_Average RMH_pos RMH_neg/solution;
random intercept/subject=bedrijf solution;
lsmeans weekdays/diff;

2. My output
Class Level Information
Class Levels Values
Bedrijf 249 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250
weekdays 5 1 2 3 4 5



Dimensions
Covariance Parameters 2
Columns in X 16
Columns in Z Per Subject 1
Subjects 249
Max Obs Per Subject 775



Number of Observations
Number of Observations Read 67755
Number of Observations Used 67730
Number of Observations Not Used 25



Iteration History
Iteration Evaluations -2 Res Log Like Criterion
0 1 -467719.3499276
1 2 -474098.6630963 0.00000000



Convergence criteria met.



Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
Intercept Bedrijf 6.247E-6 0 . .
Residual 0.000053 0 . .



Fit Statistics
-2 Res Log Likelihood -474099
AIC (smaller is better) -474095
AICC (smaller is better) -474095
BIC (smaller is better) -474088



Solution for Fixed Effects
Effect weekdays Estimate Standard Error DF t Value Pr > |t|
Intercept 0.006671 0.000231 248 28.82 <.0001
weekdays 1 0.000494 0.000088 67E3 5.60 <.0001
weekdays 2 0.000323 0.000088 67E3 3.66 0.0003
weekdays 3 0.000258 0.000088 67E3 2.93 0.0034
weekdays 4 0.000293 0.000088 67E3 3.32 0.0009
weekdays 5 0 . . . .
period1 -0.00211 0.000187 67E3 -11.27 <.0001
period2 0.000379 0.000110 67E3 3.45 0.0006
period3 0.000583 0.000076 67E3 7.64 <.0001
Stir -0.00009 0.000018 67E3 -4.99 <.0001
EMP__pos_index_retur 0.05135 0.004665 67E3 11.01 <.0001
EMP__neg_index_retur -0.07720 0.004685 67E3 -16.48 <.0001
Ltir 0.000087 0.000039 67E3 2.24 0.0254
Volatility_Average 0.2223 0.007527 67E3 29.53 <.0001
RMH_pos 0.03408 0.01126 67E3 3.03 0.0025
RMH_neg -0.07083 0.01212 67E3 -5.84 <.0001