Multiple Linear Regression - Estimated Regression Equation |
status[t] = + 2.22477 -0.00238441`MDVP:Fo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -176.913`MDVP:Jitter(%)`[t] -3321.64`MDVP:Jitter(Abs)`[t] -759.215`MDVP:RAP`[t] -36.1351`MDVP:PPQ`[t] + 360.584`Jitter:DDP`[t] + 27.4496`MDVP:Shimmer`[t] + 0.571023`MDVP:Shimmer(dB)`[t] -871.24`Shimmer:APQ3`[t] -26.3959`Shimmer:APQ5`[t] -3.07476`MDVP:APQ`[t] + 283.748`Shimmer:DDA`[t] -2.52562NHR[t] -0.0156926HNR[t] -1.01446RPDE[t] + 0.355145DFA[t] + 0.127298spread1[t] + 1.26558spread2[t] + 0.0494602D2[t] + 1.26346PPE[t] + e[t] |
Multiple Linear Regression - Ordinary Least Squares | |||||
Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
(Intercept) | 2.22477 | 1.15838 | 1.921 | 0.056438 | 0.028219 |
`MDVP:Fo(Hz)` | -0.00238441 | 0.00151006 | -1.579 | 0.116169 | 0.0580847 |
`MDVP:Fhi(Hz)` | -0.00011523 | 0.000321058 | -0.3589 | 0.720105 | 0.360053 |
`MDVP:Flo(Hz)` | -0.0015351 | 0.000802317 | -1.913 | 0.0573664 | 0.0286832 |
`MDVP:Jitter(%)` | -176.913 | 67.0287 | -2.639 | 0.00906933 | 0.00453467 |
`MDVP:Jitter(Abs)` | -3321.64 | 4625.65 | -0.7181 | 0.473676 | 0.236838 |
`MDVP:RAP` | -759.215 | 9331.88 | -0.08136 | 0.935253 | 0.467626 |
`MDVP:PPQ` | -36.1351 | 88.3839 | -0.4088 | 0.683163 | 0.341582 |
`Jitter:DDP` | 360.584 | 3111.48 | 0.1159 | 0.907876 | 0.453938 |
`MDVP:Shimmer` | 27.4496 | 34.283 | 0.8007 | 0.424424 | 0.212212 |
`MDVP:Shimmer(dB)` | 0.571023 | 1.19932 | 0.4761 | 0.634591 | 0.317295 |
`Shimmer:APQ3` | -871.24 | 8972.17 | -0.0971 | 0.922756 | 0.461378 |
`Shimmer:APQ5` | -26.3959 | 20.1229 | -1.312 | 0.191359 | 0.0956797 |
`MDVP:APQ` | -3.07476 | 10.8911 | -0.2823 | 0.778038 | 0.389019 |
`Shimmer:DDA` | 283.748 | 2989.96 | 0.0949 | 0.924505 | 0.462252 |
NHR | -2.52562 | 1.98061 | -1.275 | 0.203967 | 0.101983 |
HNR | -0.0156926 | 0.0143431 | -1.094 | 0.275444 | 0.137722 |
RPDE | -1.01446 | 0.439539 | -2.308 | 0.022189 | 0.0110945 |
DFA | 0.355145 | 0.739382 | 0.4803 | 0.631606 | 0.315803 |
spread1 | 0.127298 | 0.0978983 | 1.3 | 0.195234 | 0.0976171 |
spread2 | 1.26558 | 0.478005 | 2.648 | 0.00885943 | 0.00442971 |
D2 | 0.0494602 | 0.114324 | 0.4326 | 0.665824 | 0.332912 |
PPE | 1.26346 | 1.38335 | 0.9133 | 0.362346 | 0.181173 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.701957 |
R-squared | 0.492744 |
Adjusted R-squared | 0.427862 |
F-TEST (value) | 7.5945 |
F-TEST (DF numerator) | 22 |
F-TEST (DF denominator) | 172 |
p-value | 4.44089e-16 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 0.326672 |
Sum Squared Residuals | 18.3549 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 1 | 0.943572 | 0.0564281 |
2 | 1 | 1.07059 | -0.0705872 |
3 | 1 | 0.972611 | 0.0273892 |
4 | 1 | 1.07778 | -0.0777826 |
5 | 1 | 0.871034 | 0.128966 |
6 | 1 | 0.949455 | 0.0505448 |
7 | 1 | 0.793406 | 0.206594 |
8 | 1 | 0.580675 | 0.419325 |
9 | 1 | 0.974603 | 0.0253974 |
10 | 1 | 1.15091 | -0.15091 |
11 | 1 | 1.1116 | -0.111599 |
12 | 1 | 1.23811 | -0.238106 |
13 | 1 | 0.456882 | 0.543118 |
14 | 1 | 0.880152 | 0.119848 |
15 | 1 | 0.704846 | 0.295154 |
16 | 1 | 0.702711 | 0.297289 |
17 | 1 | 0.544442 | 0.455558 |
18 | 1 | 1.32292 | -0.322915 |
19 | 1 | 1.29341 | -0.293412 |
20 | 1 | 0.966064 | 0.0339362 |
21 | 1 | 1.06595 | -0.0659459 |
22 | 1 | 0.890474 | 0.109526 |
23 | 1 | 1.10343 | -0.103432 |
24 | 1 | 0.865771 | 0.134229 |
25 | 1 | 0.820359 | 0.179641 |
26 | 1 | 0.917409 | 0.0825911 |
27 | 1 | 0.804019 | 0.195981 |
28 | 1 | 0.7959 | 0.2041 |
29 | 1 | 0.661396 | 0.338604 |
30 | 1 | 0.699324 | 0.300676 |
31 | 0 | 0.296327 | -0.296327 |
32 | 0 | 0.159359 | -0.159359 |
33 | 0 | 0.192351 | -0.192351 |
34 | 0 | 0.128086 | -0.128086 |
35 | 0 | 0.0881745 | -0.0881745 |
36 | 0 | 0.203628 | -0.203628 |
37 | 1 | 0.810694 | 0.189306 |
38 | 1 | 0.823462 | 0.176538 |
39 | 1 | 0.596043 | 0.403957 |
40 | 1 | 0.753091 | 0.246909 |
41 | 1 | 0.612596 | 0.387404 |
42 | 1 | 0.436502 | 0.563498 |
43 | 0 | 0.244621 | -0.244621 |
44 | 0 | 0.204235 | -0.204235 |
45 | 0 | 0.0134396 | -0.0134396 |
46 | 0 | 0.0888887 | -0.0888887 |
47 | 0 | 0.0510556 | -0.0510556 |
48 | 0 | -0.0454686 | 0.0454686 |
49 | 0 | 0.337463 | -0.337463 |
50 | 0 | 0.429479 | -0.429479 |
51 | 0 | 0.410612 | -0.410612 |
52 | 0 | 0.425916 | -0.425916 |
53 | 0 | 0.411523 | -0.411523 |
54 | 0 | 0.548472 | -0.548472 |
55 | 1 | 0.827124 | 0.172876 |
56 | 1 | 0.791555 | 0.208445 |
57 | 1 | 0.867414 | 0.132586 |
58 | 1 | 0.75989 | 0.24011 |
59 | 1 | 0.77928 | 0.22072 |
60 | 1 | 0.650812 | 0.349188 |
61 | 0 | 0.369771 | -0.369771 |
62 | 0 | 0.274652 | -0.274652 |
63 | 0 | 0.264476 | -0.264476 |
64 | 0 | 0.213607 | -0.213607 |
65 | 0 | 0.128336 | -0.128336 |
66 | 0 | 0.282276 | -0.282276 |
67 | 1 | 0.91478 | 0.08522 |
68 | 1 | 0.889104 | 0.110896 |
69 | 1 | 0.92225 | 0.0777504 |
70 | 1 | 0.942369 | 0.0576308 |
71 | 1 | 0.850848 | 0.149152 |
72 | 1 | 1.093 | -0.0929953 |
73 | 1 | 0.887219 | 0.112781 |
74 | 1 | 0.922935 | 0.0770649 |
75 | 1 | 1.04227 | -0.0422683 |
76 | 1 | 1.07861 | -0.078614 |
77 | 1 | 1.09858 | -0.0985769 |
78 | 1 | 1.00048 | -0.00048325 |
79 | 1 | 0.961132 | 0.0388676 |
80 | 1 | 1.14127 | -0.141275 |
81 | 1 | 1.18014 | -0.180144 |
82 | 1 | 1.13522 | -0.13522 |
83 | 1 | 1.01365 | -0.0136507 |
84 | 1 | 0.695987 | 0.304013 |
85 | 1 | 1.08754 | -0.08754 |
86 | 1 | 0.871469 | 0.128531 |
87 | 1 | 0.703131 | 0.296869 |
88 | 1 | 0.944641 | 0.0553591 |
89 | 1 | 0.990341 | 0.00965934 |
90 | 1 | 1.22525 | -0.22525 |
91 | 1 | 1.14447 | -0.144466 |
92 | 1 | 0.797471 | 0.202529 |
93 | 1 | 0.733672 | 0.266328 |
94 | 1 | 0.853256 | 0.146744 |
95 | 1 | 0.788559 | 0.211441 |
96 | 1 | 0.757672 | 0.242328 |
97 | 1 | 0.803007 | 0.196993 |
98 | 1 | 1.0269 | -0.0269041 |
99 | 1 | 0.799739 | 0.200261 |
100 | 1 | 0.897069 | 0.102931 |
101 | 1 | 0.963853 | 0.0361472 |
102 | 1 | 0.973805 | 0.0261952 |
103 | 1 | 0.988917 | 0.011083 |
104 | 1 | 0.585775 | 0.414225 |
105 | 1 | 0.580665 | 0.419335 |
106 | 1 | 0.567264 | 0.432736 |
107 | 1 | 0.535289 | 0.464711 |
108 | 1 | 0.690104 | 0.309896 |
109 | 1 | 0.617362 | 0.382638 |
110 | 1 | 0.898421 | 0.101579 |
111 | 1 | 1.03499 | -0.0349901 |
112 | 1 | 0.589989 | 0.410011 |
113 | 1 | 0.801631 | 0.198369 |
114 | 1 | 0.698871 | 0.301129 |
115 | 1 | 0.802225 | 0.197775 |
116 | 1 | 0.885094 | 0.114906 |
117 | 1 | 0.728894 | 0.271106 |
118 | 1 | 1.05186 | -0.051857 |
119 | 1 | 0.886064 | 0.113936 |
120 | 1 | 0.761601 | 0.238399 |
121 | 1 | 0.55153 | 0.44847 |
122 | 1 | 0.973633 | 0.0263668 |
123 | 1 | 0.972849 | 0.0271515 |
124 | 1 | 0.710601 | 0.289399 |
125 | 1 | 0.61821 | 0.38179 |
126 | 1 | 0.624621 | 0.375379 |
127 | 1 | 0.612639 | 0.387361 |
128 | 1 | 0.627585 | 0.372415 |
129 | 1 | 0.414932 | 0.585068 |
130 | 1 | 0.765249 | 0.234751 |
131 | 1 | 0.803117 | 0.196883 |
132 | 1 | 0.874958 | 0.125042 |
133 | 1 | 1.05332 | -0.0533167 |
134 | 1 | 0.64704 | 0.35296 |
135 | 1 | 0.963282 | 0.0367176 |
136 | 1 | 0.961515 | 0.0384847 |
137 | 1 | 1.14637 | -0.146369 |
138 | 1 | 1.15063 | -0.150628 |
139 | 1 | 0.959753 | 0.0402465 |
140 | 1 | 0.78148 | 0.21852 |
141 | 1 | 0.910085 | 0.0899151 |
142 | 1 | 0.858298 | 0.141702 |
143 | 1 | 0.728995 | 0.271005 |
144 | 1 | 0.682826 | 0.317174 |
145 | 1 | 0.549393 | 0.450607 |
146 | 1 | 0.860233 | 0.139767 |
147 | 1 | 1.35151 | -0.351514 |
148 | 1 | 1.15229 | -0.152285 |
149 | 1 | 1.24477 | -0.244774 |
150 | 1 | 0.893702 | 0.106298 |
151 | 1 | 0.934253 | 0.065747 |
152 | 1 | 0.955932 | 0.0440683 |
153 | 1 | 0.95908 | 0.0409204 |
154 | 1 | 0.845406 | 0.154594 |
155 | 1 | 0.894439 | 0.105561 |
156 | 1 | 0.994817 | 0.00518265 |
157 | 1 | 0.798684 | 0.201316 |
158 | 1 | 1.2687 | -0.268698 |
159 | 1 | 0.970747 | 0.0292526 |
160 | 1 | 0.8619 | 0.1381 |
161 | 1 | 1.12813 | -0.128132 |
162 | 1 | 1.05871 | -0.0587125 |
163 | 1 | 0.930825 | 0.0691748 |
164 | 1 | 0.794176 | 0.205824 |
165 | 1 | 1.38244 | -0.382443 |
166 | 0 | 0.450212 | -0.450212 |
167 | 0 | 0.225191 | -0.225191 |
168 | 0 | 0.0938475 | -0.0938475 |
169 | 0 | 0.941843 | -0.941843 |
170 | 0 | 0.230278 | -0.230278 |
171 | 0 | 0.114576 | -0.114576 |
172 | 0 | 0.799341 | -0.799341 |
173 | 0 | 0.835874 | -0.835874 |
174 | 0 | 0.878334 | -0.878334 |
175 | 0 | 0.86601 | -0.86601 |
176 | 0 | 0.834631 | -0.834631 |
177 | 0 | 0.776849 | -0.776849 |
178 | 1 | 0.64434 | 0.35566 |
179 | 1 | 0.712233 | 0.287767 |
180 | 1 | 0.934324 | 0.0656761 |
181 | 1 | 0.763979 | 0.236021 |
182 | 1 | 0.872426 | 0.127574 |
183 | 1 | 0.719193 | 0.280807 |
184 | 0 | 0.604386 | -0.604386 |
185 | 0 | 0.648463 | -0.648463 |
186 | 0 | 0.606784 | -0.606784 |
187 | 0 | 0.423249 | -0.423249 |
188 | 0 | 0.475362 | -0.475362 |
189 | 0 | 0.435997 | -0.435997 |
190 | 0 | 0.428277 | -0.428277 |
191 | 0 | 0.651129 | -0.651129 |
192 | 0 | 0.700978 | -0.700978 |
193 | 0 | -0.174504 | 0.174504 |
194 | 0 | 0.267081 | -0.267081 |
195 | 0 | 0.519415 | -0.519415 |
Goldfeld-Quandt test for Heteroskedasticity | |||
p-values | Alternative Hypothesis | ||
breakpoint index | greater | 2-sided | less |
26 | 1.81438e-53 | 3.62877e-53 | 1 |
27 | 3.49729e-65 | 6.99458e-65 | 1 |
28 | 9.12368e-78 | 1.82474e-77 | 1 |
29 | 3.41667e-94 | 6.83333e-94 | 1 |
30 | 4.4197e-110 | 8.8394e-110 | 1 |
31 | 0.000254625 | 0.000509251 | 0.999745 |
32 | 6.62847e-05 | 0.000132569 | 0.999934 |
33 | 1.63455e-05 | 3.2691e-05 | 0.999984 |
34 | 4.92124e-06 | 9.84249e-06 | 0.999995 |
35 | 1.49305e-06 | 2.98611e-06 | 0.999999 |
36 | 3.66378e-07 | 7.32756e-07 | 1 |
37 | 5.20394e-05 | 0.000104079 | 0.999948 |
38 | 2.99681e-05 | 5.99362e-05 | 0.99997 |
39 | 0.000527844 | 0.00105569 | 0.999472 |
40 | 0.000867612 | 0.00173522 | 0.999132 |
41 | 0.00108903 | 0.00217805 | 0.998911 |
42 | 0.000634559 | 0.00126912 | 0.999365 |
43 | 0.00039109 | 0.000782179 | 0.999609 |
44 | 0.000218868 | 0.000437736 | 0.999781 |
45 | 0.000101994 | 0.000203987 | 0.999898 |
46 | 5.00692e-05 | 0.000100138 | 0.99995 |
47 | 2.99692e-05 | 5.99383e-05 | 0.99997 |
48 | 3.98807e-05 | 7.97614e-05 | 0.99996 |
49 | 0.000174357 | 0.000348714 | 0.999826 |
50 | 0.000143821 | 0.000287642 | 0.999856 |
51 | 9.51895e-05 | 0.000190379 | 0.999905 |
52 | 6.31252e-05 | 0.00012625 | 0.999937 |
53 | 4.43579e-05 | 8.87159e-05 | 0.999956 |
54 | 4.61595e-05 | 9.23189e-05 | 0.999954 |
55 | 5.31699e-05 | 0.00010634 | 0.999947 |
56 | 6.6546e-05 | 0.000133092 | 0.999933 |
57 | 3.76979e-05 | 7.53957e-05 | 0.999962 |
58 | 2.59914e-05 | 5.19829e-05 | 0.999974 |
59 | 1.47526e-05 | 2.95051e-05 | 0.999985 |
60 | 8.44088e-06 | 1.68818e-05 | 0.999992 |
61 | 0.000351734 | 0.000703468 | 0.999648 |
62 | 0.00045714 | 0.000914281 | 0.999543 |
63 | 0.000623591 | 0.00124718 | 0.999376 |
64 | 0.000623241 | 0.00124648 | 0.999377 |
65 | 0.000426082 | 0.000852164 | 0.999574 |
66 | 0.000422082 | 0.000844164 | 0.999578 |
67 | 0.000283262 | 0.000566525 | 0.999717 |
68 | 0.000182397 | 0.000364794 | 0.999818 |
69 | 0.000231628 | 0.000463256 | 0.999768 |
70 | 0.000178608 | 0.000357216 | 0.999821 |
71 | 0.000107865 | 0.000215731 | 0.999892 |
72 | 7.36296e-05 | 0.000147259 | 0.999926 |
73 | 4.32049e-05 | 8.64097e-05 | 0.999957 |
74 | 0.000119608 | 0.000239216 | 0.99988 |
75 | 0.000156398 | 0.000312795 | 0.999844 |
76 | 0.000115769 | 0.000231539 | 0.999884 |
77 | 7.49724e-05 | 0.000149945 | 0.999925 |
78 | 5.88101e-05 | 0.00011762 | 0.999941 |
79 | 3.48878e-05 | 6.97756e-05 | 0.999965 |
80 | 2.49067e-05 | 4.98133e-05 | 0.999975 |
81 | 1.84899e-05 | 3.69798e-05 | 0.999982 |
82 | 1.07743e-05 | 2.15486e-05 | 0.999989 |
83 | 7.13072e-06 | 1.42614e-05 | 0.999993 |
84 | 4.57944e-06 | 9.15887e-06 | 0.999995 |
85 | 2.76835e-06 | 5.53669e-06 | 0.999997 |
86 | 3.23318e-06 | 6.46637e-06 | 0.999997 |
87 | 5.28066e-06 | 1.05613e-05 | 0.999995 |
88 | 3.34163e-06 | 6.68327e-06 | 0.999997 |
89 | 2.59786e-06 | 5.19572e-06 | 0.999997 |
90 | 3.2149e-06 | 6.42979e-06 | 0.999997 |
91 | 3.17262e-06 | 6.34524e-06 | 0.999997 |
92 | 3.96138e-06 | 7.92276e-06 | 0.999996 |
93 | 2.51952e-06 | 5.03904e-06 | 0.999997 |
94 | 1.68852e-06 | 3.37705e-06 | 0.999998 |
95 | 1.0897e-06 | 2.17939e-06 | 0.999999 |
96 | 6.75617e-07 | 1.35123e-06 | 0.999999 |
97 | 4.20086e-07 | 8.40171e-07 | 1 |
98 | 2.39384e-07 | 4.78768e-07 | 1 |
99 | 1.48975e-07 | 2.9795e-07 | 1 |
100 | 8.73995e-08 | 1.74799e-07 | 1 |
101 | 6.86125e-08 | 1.37225e-07 | 1 |
102 | 6.59206e-08 | 1.31841e-07 | 1 |
103 | 7.73713e-08 | 1.54743e-07 | 1 |
104 | 1.48816e-07 | 2.97633e-07 | 1 |
105 | 2.30966e-07 | 4.61932e-07 | 1 |
106 | 4.22015e-07 | 8.44031e-07 | 1 |
107 | 9.9405e-07 | 1.9881e-06 | 0.999999 |
108 | 7.28182e-07 | 1.45636e-06 | 0.999999 |
109 | 1.65514e-06 | 3.31029e-06 | 0.999998 |
110 | 1.35674e-06 | 2.71347e-06 | 0.999999 |
111 | 8.08882e-07 | 1.61776e-06 | 0.999999 |
112 | 1.63893e-06 | 3.27786e-06 | 0.999998 |
113 | 1.08425e-06 | 2.16849e-06 | 0.999999 |
114 | 1.26298e-06 | 2.52596e-06 | 0.999999 |
115 | 1.24807e-06 | 2.49613e-06 | 0.999999 |
116 | 8.45062e-07 | 1.69012e-06 | 0.999999 |
117 | 1.16203e-06 | 2.32406e-06 | 0.999999 |
118 | 6.70629e-07 | 1.34126e-06 | 0.999999 |
119 | 4.73737e-07 | 9.47475e-07 | 1 |
120 | 1.08744e-06 | 2.17488e-06 | 0.999999 |
121 | 6.79345e-06 | 1.35869e-05 | 0.999993 |
122 | 1.71457e-05 | 3.42914e-05 | 0.999983 |
123 | 1.09449e-05 | 2.18899e-05 | 0.999989 |
124 | 7.51178e-06 | 1.50236e-05 | 0.999992 |
125 | 5.28317e-06 | 1.05663e-05 | 0.999995 |
126 | 5.53159e-06 | 1.10632e-05 | 0.999994 |
127 | 1.11081e-05 | 2.22162e-05 | 0.999989 |
128 | 0.000146257 | 0.000292514 | 0.999854 |
129 | 0.000382556 | 0.000765111 | 0.999617 |
130 | 0.000487417 | 0.000974833 | 0.999513 |
131 | 0.000501867 | 0.00100373 | 0.999498 |
132 | 0.000343465 | 0.00068693 | 0.999657 |
133 | 0.000307967 | 0.000615934 | 0.999692 |
134 | 0.00138302 | 0.00276605 | 0.998617 |
135 | 0.00160607 | 0.00321214 | 0.998394 |
136 | 0.00156328 | 0.00312657 | 0.998437 |
137 | 0.00168985 | 0.0033797 | 0.99831 |
138 | 0.00173573 | 0.00347146 | 0.998264 |
139 | 0.0011725 | 0.00234499 | 0.998828 |
140 | 0.00145352 | 0.00290705 | 0.998546 |
141 | 0.00122873 | 0.00245746 | 0.998771 |
142 | 0.00156404 | 0.00312807 | 0.998436 |
143 | 0.00131453 | 0.00262906 | 0.998685 |
144 | 0.00451619 | 0.00903238 | 0.995484 |
145 | 0.00392027 | 0.00784053 | 0.99608 |
146 | 0.00301649 | 0.00603298 | 0.996984 |
147 | 0.00214546 | 0.00429093 | 0.997855 |
148 | 0.00138353 | 0.00276706 | 0.998616 |
149 | 0.001399 | 0.002798 | 0.998601 |
150 | 0.000927437 | 0.00185487 | 0.999073 |
151 | 0.000869116 | 0.00173823 | 0.999131 |
152 | 0.00638518 | 0.0127704 | 0.993615 |
153 | 0.034277 | 0.068554 | 0.965723 |
154 | 0.0305368 | 0.0610736 | 0.969463 |
155 | 0.0258451 | 0.0516903 | 0.974155 |
156 | 0.0192208 | 0.0384417 | 0.980779 |
157 | 0.0890786 | 0.178157 | 0.910921 |
158 | 0.0842521 | 0.168504 | 0.915748 |
159 | 0.287358 | 0.574716 | 0.712642 |
160 | 0.226367 | 0.452733 | 0.773633 |
161 | 0.169916 | 0.339833 | 0.830084 |
162 | 0.129257 | 0.258514 | 0.870743 |
163 | 0.147854 | 0.295709 | 0.852146 |
164 | 0.316125 | 0.63225 | 0.683875 |
165 | 0.425348 | 0.850696 | 0.574652 |
166 | 0.520868 | 0.958265 | 0.479132 |
167 | 0.901752 | 0.196496 | 0.0982482 |
168 | 0.945003 | 0.109993 | 0.0549967 |
169 | 0.962954 | 0.0740914 | 0.0370457 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
Description | # significant tests | % significant tests | OK/NOK |
1% type I error level | 126 | 0.875 | NOK |
5% type I error level | 128 | 0.888889 | NOK |
10% type I error level | 132 | 0.916667 | NOK |