Analysis
Experiment 1 With spatial cues
1 Sagittal
##
## Call:
## lm(formula = percent ~ hatch_condition, data = df.accSpatial %>%
## subset(test == "sagittal"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.44 -6.89 1.56 4.36 18.62
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 28.44 1.79 15.85 <2e-16 ***
## hatch_conditionlight 7.95 2.54 3.13 0.003 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.79 on 46 degrees of freedom
## Multiple R-squared: 0.176, Adjusted R-squared: 0.158
## F-statistic: 9.81 on 1 and 46 DF, p-value: 0.00302## Bayes factor analysis
## --------------
## [1] hatch_condition : 12.6 ±0%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS1 FP binocular
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accSpatial %>%
## subset(test == "FP binocular"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -23.41 -8.41 -0.45 6.59 34.66
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.344 2.039 7.53 3.3e-11 ***
## hatch_conditionlight 0.998 2.354 0.42 0.67262
## choice4L 8.062 2.354 3.42 0.00092 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 11.5 on 93 degrees of freedom
## Multiple R-squared: 0.114, Adjusted R-squared: 0.0945
## F-statistic: 5.95 on 2 and 93 DF, p-value: 0.00369##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accSpatial %>%
## subset(test == "FP binocular"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -23.85 -6.89 -1.89 6.15 30.21
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 19.792 2.177 9.09 1.9e-14 ***
## hatch_conditionlight -7.897 3.079 -2.56 0.012 *
## choice4L -0.833 3.079 -0.27 0.787
## hatch_conditionlight:choice4L 17.790 4.355 4.09 9.4e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.7 on 92 degrees of freedom
## Multiple R-squared: 0.25, Adjusted R-squared: 0.225
## F-statistic: 10.2 on 3 and 92 DF, p-value: 7.27e-06## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light 7.90 3.08 92 2.560 0.0120
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light -9.89 3.08 92 -3.210 0.0018## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 0.83 3.08 92 0.270 0.7870
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -16.96 3.08 92 -5.510 <.0001## Bayes factor analysis
## --------------
## [1] hatch_condition : 0.231 ±0.02%
## [2] choice : 33.5 ±0%
## [3] hatch_condition + choice : 7.7 ±1.59%
## [4] hatch_condition + choice + hatch_condition:choice : 1782 ±4.08%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 235 ±2.39%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZS1 FP left
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accSpatial %>%
## subset(test == "FP left"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -14.66 -4.66 -2.11 5.34 19.28
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.11 1.37 1.54 0.12684
## hatch_conditionlight 6.06 1.58 3.83 0.00024 ***
## choice4L 12.54 1.58 7.92 5e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.76 on 93 degrees of freedom
## Multiple R-squared: 0.454, Adjusted R-squared: 0.442
## F-statistic: 38.7 on 2 and 93 DF, p-value: 5.96e-13##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accSpatial %>%
## subset(test == "FP left"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.78 -4.42 -1.61 4.81 17.41
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.99 1.54 2.58 0.01131 *
## hatch_conditionlight 2.31 2.18 1.06 0.29345
## choice4L 8.79 2.18 4.03 0.00012 ***
## hatch_conditionlight:choice4L 7.51 3.09 2.43 0.01696 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.56 on 92 degrees of freedom
## Multiple R-squared: 0.487, Adjusted R-squared: 0.47
## F-statistic: 29.1 on 3 and 92 DF, p-value: 2.5e-13## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light -2.31 2.18 92 -1.060 0.2934
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light -9.81 2.18 92 -4.500 <.0001## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -8.79 2.18 92 -4.030 0.0001
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -16.30 2.18 92 -7.470 <.0001## Bayes factor analysis
## --------------
## [1] hatch_condition : 9.7 ±0%
## [2] choice : 127725862 ±0%
## [3] hatch_condition + choice : 1.27e+10 ±3.54%
## [4] hatch_condition + choice + hatch_condition:choice : 3.86e+10 ±1.06%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 3.09 ±1.38%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZS1 FP right
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accSpatial %>%
## subset(test == "FP right"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -19.84 -5.07 -1.29 4.33 20.16
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.07 1.41 10.68 < 2e-16 ***
## hatch_conditionlight 4.77 1.63 2.93 0.0043 **
## choice4L -12.97 1.63 -7.96 4.1e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.98 on 93 degrees of freedom
## Multiple R-squared: 0.436, Adjusted R-squared: 0.424
## F-statistic: 36 on 2 and 93 DF, p-value: 2.68e-12##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accSpatial %>%
## subset(test == "FP right"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.484 -4.114 -0.219 3.069 18.516
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 13.42 1.60 8.38 5.9e-13 ***
## hatch_conditionlight 8.07 2.26 3.56 0.00058 ***
## choice4L -9.67 2.26 -4.27 4.7e-05 ***
## hatch_conditionlight:choice4L -6.60 3.20 -2.06 0.04230 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.85 on 92 degrees of freedom
## Multiple R-squared: 0.461, Adjusted R-squared: 0.443
## F-statistic: 26.2 on 3 and 92 DF, p-value: 2.38e-12## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light -8.07 2.27 92 -3.560 0.0010
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light -1.47 2.27 92 -0.650 0.5170## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 9.67 2.27 92 4.270 <.0001
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 16.27 2.27 92 7.180 <.0001## Bayes factor analysis
## --------------
## [1] hatch_condition : 2.04 ±0.01%
## [2] choice : 408086481 ±0%
## [3] hatch_condition + choice : 3.31e+09 ±1.94%
## [4] hatch_condition + choice + hatch_condition:choice : 5.42e+09 ±1.1%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 1.65 ±1.91%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZSExperiment 2 (without spatial cues)
2 sagittal
##
## Call:
## lm(formula = percent ~ hatch_condition, data = df.accNON %>%
## subset(test == "sagittal"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -26.49 -7.27 -1.88 7.73 33.51
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 31.487 2.636 11.94 2.9e-16 ***
## hatch_conditionlight 0.788 3.728 0.21 0.83
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13.4 on 50 degrees of freedom
## Multiple R-squared: 0.000893, Adjusted R-squared: -0.0191
## F-statistic: 0.0447 on 1 and 50 DF, p-value: 0.833## Bayes factor analysis
## --------------
## [1] hatch_condition : 0.283 ±0.01%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS2 FP binocular
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accNON %>%
## subset(test == "FP binocular"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.453 -7.528 -0.453 6.163 24.957
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 17.94 1.65 10.87 <2e-16 ***
## hatch_conditionlight -0.41 1.91 -0.22 0.83
## choice4L 2.52 1.91 1.32 0.19
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.72 on 101 degrees of freedom
## Multiple R-squared: 0.0174, Adjusted R-squared: -0.00206
## F-statistic: 0.894 on 2 and 101 DF, p-value: 0.412##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accNON %>%
## subset(test == "FP binocular"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -19.67 -6.77 1.27 6.28 23.23
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 19.666 1.884 10.44 <2e-16 ***
## hatch_conditionlight -3.866 2.664 -1.45 0.15
## choice4L -0.941 2.664 -0.35 0.72
## hatch_conditionlight:choice4L 6.913 3.768 1.83 0.07 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.61 on 100 degrees of freedom
## Multiple R-squared: 0.0494, Adjusted R-squared: 0.0209
## F-statistic: 1.73 on 3 and 100 DF, p-value: 0.165## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light 3.87 2.66 100 1.451 0.1499
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light -3.05 2.66 100 -1.143 0.2556## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 0.94 2.66 100 0.353 0.7250
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -5.97 2.66 100 -2.241 0.0270## Bayes factor analysis
## --------------
## [1] hatch_condition : 0.211 ±0.03%
## [2] choice : 0.453 ±0.02%
## [3] hatch_condition + choice : 0.0925 ±1.47%
## [4] hatch_condition + choice + hatch_condition:choice : 0.109 ±1.25%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 1.15 ±1.87%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZS2 FP left
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accNON %>%
## subset(test == "FP left"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -14.978 -4.978 0.131 5.367 20.317
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.190 1.388 5.90 4.8e-08 ***
## hatch_conditionlight -0.109 1.602 -0.07 0.95
## choice4L 6.787 1.602 4.24 5.0e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.17 on 101 degrees of freedom
## Multiple R-squared: 0.151, Adjusted R-squared: 0.134
## F-statistic: 8.97 on 2 and 101 DF, p-value: 0.000259##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accNON %>%
## subset(test == "FP left"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -15.011 -4.879 -0.011 5.362 20.459
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.333 1.610 5.18 1.2e-06 ***
## hatch_conditionlight -0.394 2.277 -0.17 0.8631
## choice4L 6.502 2.277 2.86 0.0052 **
## hatch_conditionlight:choice4L 0.570 3.220 0.18 0.8599
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.21 on 100 degrees of freedom
## Multiple R-squared: 0.151, Adjusted R-squared: 0.126
## F-statistic: 5.93 on 3 and 100 DF, p-value: 0.00091## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light 0.394 2.28 100 0.173 0.8630
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light -0.176 2.28 100 -0.077 0.9380## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -6.50 2.28 100 -2.855 0.0052
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L -7.07 2.28 100 -3.106 0.0025## Bayes factor analysis
## --------------
## [1] hatch_condition : 0.208 ±0.03%
## [2] choice : 436 ±0%
## [3] hatch_condition + choice : 87 ±1.54%
## [4] hatch_condition + choice + hatch_condition:choice : 23.8 ±1.58%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 0.301 ±1.9%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZS2 FP right
##
## Call:
## lm(formula = percent ~ hatch_condition + choice, data = df.accNON %>%
## subset(test == "FP right"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -14.34 -6.41 -1.41 5.43 23.59
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14.34 1.44 9.97 < 2e-16 ***
## hatch_conditionlight 1.76 1.66 1.06 0.29
## choice4L -7.93 1.66 -4.78 6.1e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.47 on 101 degrees of freedom
## Multiple R-squared: 0.192, Adjusted R-squared: 0.176
## F-statistic: 12 on 2 and 101 DF, p-value: 0.0000217##
## Call:
## lm(formula = percent ~ hatch_condition * choice, data = df.accNON %>%
## subset(test == "FP right"))
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.98 -6.29 -2.12 5.65 21.71
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.46 1.63 7.66 1.2e-11 ***
## hatch_conditionlight 5.53 2.30 2.40 0.018 *
## choice4L -4.17 2.30 -1.81 0.073 .
## hatch_conditionlight:choice4L -7.53 3.25 -2.32 0.023 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.29 on 100 degrees of freedom
## Multiple R-squared: 0.233, Adjusted R-squared: 0.21
## F-statistic: 10.1 on 3 and 100 DF, p-value: 7.08e-06## choice = 4R:
## contrast estimate SE df t.ratio p.value
## dark - light -5.53 2.3 100 -2.404 0.0180
##
## choice = 4L:
## contrast estimate SE df t.ratio p.value
## dark - light 2.00 2.3 100 0.871 0.3860## hatch_condition = dark:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 4.17 2.3 100 1.810 0.0730
##
## hatch_condition = light:
## contrast estimate SE df t.ratio p.value
## 4R - 4L 11.70 2.3 100 5.090 <.0001## Bayes factor analysis
## --------------
## [1] hatch_condition : 0.313 ±0.02%
## [2] choice : 2707 ±0%
## [3] hatch_condition + choice : 915 ±3.33%
## [4] hatch_condition + choice + hatch_condition:choice : 2225 ±1.94%
##
## Against denominator:
## Intercept only
## ---
## Bayes factor type: BFlinearModel, JZS## Bayes factor analysis
## --------------
## [1] hatch_condition * choice + hatch_condition + choice : 2.35 ±5.82%
##
## Against denominator:
## percent ~ hatch_condition + choice
## ---
## Bayes factor type: BFlinearModel, JZSt tests
4L vs. 4R
4L - 4R
| spatialCue | lateralization | test | bf | t | p | CI_lower | CI_upper | mean_difference |
|---|---|---|---|---|---|---|---|---|
| NONspatial | dark | FP binocular | 0.216 | -0.300 | 0.767 | -7.401 | 5.518 | -0.941 |
| NONspatial | dark | FP left | 2.145 | 2.369 | 0.026 | 0.850 | 12.155 | 6.502 |
| NONspatial | dark | FP right | 0.705 | -1.674 | 0.107 | -9.293 | 0.959 | -4.167 |
| NONspatial | light | FP binocular | 0.997 | 1.910 | 0.068 | -0.466 | 12.409 | 5.972 |
| NONspatial | light | FP left | 8.890 | 3.100 | 0.005 | 2.373 | 11.771 | 7.072 |
| NONspatial | light | FP right | 573.520 | -4.946 | 0.000 | -16.567 | -6.826 | -11.697 |
| spatial | dark | FP binocular | 0.219 | -0.218 | 0.830 | -8.749 | 7.083 | -0.833 |
| spatial | dark | FP left | 299.195 | 4.738 | 0.000 | 4.952 | 12.628 | 8.790 |
| spatial | dark | FP right | 243.206 | -4.645 | 0.000 | -13.977 | -5.364 | -9.670 |
| spatial | light | FP binocular | 337.124 | 4.791 | 0.000 | 9.636 | 24.278 | 16.957 |
| spatial | light | FP left | 5598.452 | 6.056 | 0.000 | 10.731 | 21.865 | 16.298 |
| spatial | light | FP right | 6887.511 | -6.151 | 0.000 | -21.736 | -10.795 | -16.265 |
strong vs. weak lateralized
strong - weak
| spatialCue | test_choice | bf | t | p | CI_lower | CI_upper | mean_strong | mean_weak |
|---|---|---|---|---|---|---|---|---|
| NONspatial | sag_4 | 0.283 | 0.211 | 0.834 | -6.717 | 8.29 | 32.27 | 31.49 |
| NONspatial | bin_4L | 0.478 | 1.147 | 0.257 | -2.287 | 8.38 | 21.77 | 18.73 |
| NONspatial | bin_4R | 0.655 | -1.446 | 0.154 | -9.237 | 1.50 | 15.80 | 19.67 |
| NONspatial | sx_4L | 0.279 | 0.066 | 0.948 | -5.180 | 5.53 | 15.01 | 14.84 |
| NONspatial | sx_4R | 0.284 | -0.218 | 0.828 | -4.022 | 3.23 | 7.94 | 8.33 |
| NONspatial | dx_4L | 0.434 | -1.039 | 0.304 | -5.876 | 1.87 | 6.29 | 8.29 |
| NONspatial | dx_4R | 1.678 | 2.110 | 0.040 | 0.265 | 10.79 | 17.98 | 12.46 |
| spatial | sag_4 | 12.588 | 3.132 | 0.003 | 2.836 | 13.06 | 36.38 | 28.44 |
| spatial | bin_4L | 8.456 | 2.952 | 0.005 | 3.141 | 16.64 | 28.85 | 18.96 |
| spatial | bin_4R | 6.657 | -2.840 | 0.007 | -13.518 | -2.28 | 11.89 | 19.79 |
| spatial | sx_4L | 104.830 | 3.988 | 0.000 | 4.860 | 14.77 | 22.59 | 12.78 |
| spatial | sx_4R | 0.535 | 1.237 | 0.222 | -1.446 | 6.06 | 6.30 | 3.99 |
| spatial | dx_4L | 0.426 | 0.983 | 0.332 | -1.563 | 4.51 | 5.22 | 3.75 |
| spatial | dx_4R | 6.799 | 2.850 | 0.007 | 2.363 | 13.77 | 21.48 | 13.42 |
spatial vs. non spatial
spatial - non spatial
| lateralization | test_choice | bf | t | p | CI_lower | CI_upper | mean_spatial | mean_nonspatial |
|---|---|---|---|---|---|---|---|---|
| dark | sag_4 | 0.378 | -0.856 | 0.397 | -10.246 | 4.143 | 28.44 | 31.49 |
| dark | bin_4L | 0.284 | 0.083 | 0.934 | -5.426 | 5.893 | 18.96 | 18.73 |
| dark | bin_4R | 0.283 | 0.041 | 0.967 | -5.997 | 6.248 | 19.79 | 19.67 |
| dark | sx_4L | 0.366 | -0.798 | 0.429 | -7.233 | 3.123 | 12.78 | 14.84 |
| dark | sx_4R | 2.505 | -2.350 | 0.023 | -8.059 | -0.627 | 3.99 | 8.33 |
| dark | dx_4L | 4.432 | -2.707 | 0.010 | -7.946 | -1.141 | 3.75 | 8.29 |
| dark | dx_4R | 0.300 | 0.376 | 0.708 | -4.169 | 6.089 | 13.42 | 12.46 |
| light | sag_4 | 0.680 | 1.487 | 0.144 | -1.454 | 9.668 | 36.38 | 32.27 |
| light | bin_4L | 2.030 | 2.198 | 0.033 | 0.587 | 13.573 | 28.85 | 21.77 |
| light | bin_4R | 0.833 | -1.646 | 0.106 | -8.677 | 0.867 | 11.89 | 15.80 |
| light | sx_4L | 8.647 | 2.966 | 0.005 | 2.442 | 12.725 | 22.59 | 15.01 |
| light | sx_4R | 0.396 | -0.902 | 0.372 | -5.309 | 2.024 | 6.30 | 7.94 |
| light | dx_4L | 0.329 | -0.603 | 0.549 | -4.632 | 2.494 | 5.22 | 6.29 |
| light | dx_4R | 0.517 | 1.210 | 0.232 | -2.322 | 9.323 | 21.48 | 17.98 |
chance exp1
## test hatch_condition choice Mean sd n se r p
## 1 FP binocular dark 1L 6.46 8.27 24 1.689 -0.47300 0.987
## 2 FP binocular dark 1R 6.25 5.57 24 1.136 -0.59100 0.997
## 3 FP binocular dark 2L 9.58 7.79 24 1.590 -0.05800 0.606
## 4 FP binocular dark 2R 5.83 6.02 24 1.229 -0.62600 0.995
## 5 FP binocular dark 3L 7.29 5.10 24 1.042 -0.53900 0.991
## 6 FP binocular dark 3R 6.46 5.61 24 1.145 -0.62600 0.995
## 7 FP binocular dark 4L 18.96 10.53 24 2.149 0.72700 0.000458
## 8 FP binocular dark 4R 19.79 11.37 24 2.321 0.72400 0.000276
## 9 FP binocular dark 5L 9.79 6.16 24 1.258 -0.00597 0.52
## 10 FP binocular dark 5R 9.58 5.88 24 1.201 -0.12700 0.713
## 11 FP binocular light 1L 5.10 5.60 24 1.143 -0.70400 0.999
## 12 FP binocular light 1R 7.35 6.75 24 1.378 -0.45200 0.962
## 13 FP binocular light 2L 8.02 7.19 24 1.467 -0.34200 0.94
## 14 FP binocular light 2R 7.16 6.44 24 1.315 -0.36500 0.958
## 15 FP binocular light 3L 6.58 5.78 24 1.180 -0.57000 0.993
## 16 FP binocular light 3R 7.79 7.91 24 1.614 -0.27700 0.896
## 17 FP binocular light 4L 28.85 12.60 24 2.572 0.85900 0.0000137
## 18 FP binocular light 4R 11.89 7.50 24 1.532 0.33700 0.0798
## 19 FP binocular light 5L 10.18 7.01 24 1.431 0.02570 0.462
## 20 FP binocular light 5R 7.08 6.26 24 1.278 -0.43600 0.976
## 21 FP left dark 1L 31.59 18.40 24 3.755 0.82600 0.0000403
## 22 FP left dark 1R 5.72 9.51 24 1.942 -0.44900 0.987
## 23 FP left dark 2L 17.33 9.62 24 1.964 0.68300 0.00092
## 24 FP left dark 2R 2.78 4.94 24 1.009 -0.81300 1
## 25 FP left dark 3L 11.91 9.77 24 1.995 0.18900 0.205
## 26 FP left dark 3R 2.35 3.65 24 0.745 -0.85900 1
## 27 FP left dark 4L 12.78 8.31 24 1.696 0.37600 0.0532
## 28 FP left dark 4R 3.99 6.15 24 1.256 -0.70800 1
## 29 FP left dark 5L 6.63 7.23 24 1.475 -0.44600 0.982
## 30 FP left dark 5R 4.94 4.56 24 0.931 -0.80300 1
## 31 FP left light 1L 23.04 10.53 24 2.150 0.86300 0.0000124
## 32 FP left light 1R 6.26 6.62 24 1.350 -0.54400 0.995
## 33 FP left light 2L 11.11 7.27 24 1.484 0.17100 0.21
## 34 FP left light 2R 3.24 4.11 24 0.839 -0.85100 1
## 35 FP left light 3L 12.50 7.11 24 1.451 0.35700 0.0455
## 36 FP left light 3R 3.64 5.89 24 1.202 -0.72800 1
## 37 FP left light 4L 22.59 8.74 24 1.783 0.87600 0.0000144
## 38 FP left light 4R 6.30 6.75 24 1.377 -0.46500 0.988
## 39 FP left light 5L 7.58 7.19 24 1.468 -0.37900 0.967
## 40 FP left light 5R 3.74 4.77 24 0.974 -0.80300 1
## 41 FP right dark 1L 3.99 4.71 24 0.961 -0.82300 1
## 42 FP right dark 1R 33.74 16.55 24 3.377 0.86100 0.0000132
## 43 FP right dark 2L 2.76 4.74 24 0.967 -0.87200 1
## 44 FP right dark 2R 15.78 12.80 24 2.613 0.41100 0.0255
## 45 FP right dark 3L 4.08 5.95 24 1.214 -0.72900 1
## 46 FP right dark 3R 9.54 8.19 24 1.672 -0.03840 0.578
## 47 FP right dark 4L 3.75 3.67 24 0.749 -0.79800 1
## 48 FP right dark 4R 13.42 8.78 24 1.792 0.40600 0.0398
## 49 FP right dark 5L 5.03 5.00 24 1.022 -0.71600 1
## 50 FP right dark 5R 7.91 6.33 24 1.292 -0.30400 0.905
## 51 FP right light 1L 5.37 7.54 24 1.539 -0.61300 0.998
## 52 FP right light 1R 23.77 14.39 24 2.937 0.76500 0.000176
## 53 FP right light 2L 4.35 5.66 24 1.156 -0.76800 1
## 54 FP right light 2R 13.85 9.45 24 1.928 0.41900 0.0287
## 55 FP right light 3L 4.41 5.20 24 1.062 -0.75900 1
## 56 FP right light 3R 11.26 5.86 24 1.196 0.29300 0.0984
## 57 FP right light 4L 5.22 6.36 24 1.297 -0.59400 0.998
## 58 FP right light 4R 21.48 10.73 24 2.191 0.80700 0.000114
## 59 FP right light 5L 5.99 4.64 24 0.947 -0.68500 0.999
## 60 FP right light 5R 4.30 4.76 24 0.971 -0.77200 1
## 61 sagittal dark 1 17.15 10.58 24 2.159 0.65100 0.00194
## 62 sagittal dark 10 2.29 3.29 24 0.672 -0.91200 1
## 63 sagittal dark 2 15.38 8.41 24 1.716 0.68200 0.00269
## 64 sagittal dark 3 11.29 7.02 24 1.432 0.22700 0.166
## 65 sagittal dark 4 28.44 9.37 24 1.913 0.87800 9.11e-06
## 66 sagittal dark 5 7.99 5.79 24 1.183 -0.34500 0.92
## 67 sagittal dark 6 7.33 6.90 24 1.409 -0.39500 0.959
## 68 sagittal dark 7 5.91 5.18 24 1.057 -0.73200 0.998
## 69 sagittal dark 8 2.55 4.00 24 0.816 -0.91700 1
## 70 sagittal dark 9 1.68 2.42 24 0.495 -0.91000 1
## 71 sagittal light 1 14.65 8.39 24 1.713 0.56900 0.00698
## 72 sagittal light 10 1.26 2.23 24 0.456 -0.92300 1
## 73 sagittal light 2 18.63 8.57 24 1.748 0.82800 0.000168
## 74 sagittal light 3 9.00 6.78 24 1.384 -0.09430 0.667
## 75 sagittal light 4 36.38 8.16 24 1.666 0.88000 8.83e-06
## 76 sagittal light 5 4.97 4.60 24 0.938 -0.78300 1
## 77 sagittal light 6 5.91 6.70 24 1.368 -0.57000 0.995
## 78 sagittal light 7 4.58 6.74 24 1.376 -0.70400 1
## 79 sagittal light 8 2.51 4.67 24 0.953 -0.82200 1
## 80 sagittal light 9 2.09 2.93 24 0.598 -0.90900 1
## p.adj bf ES.h p.sig p.adj.sig bf_cat
## 1 1.0000000 7.83e-02 -0.6435 ns ns <NA>
## 2 1.0000000 6.02e-02 -0.1925 ns ns <NA>
## 3 1.0000000 1.78e-01 -0.6435 ns ns <NA>
## 4 1.0000000 5.93e-02 0.0000 ns ns <NA>
## 5 1.0000000 6.90e-02 -0.6435 ns ns <NA>
## 6 1.0000000 6.24e-02 0.0567 ns ns <NA>
## 7 0.0045776 1.69e+02 0.1519 *** ** Extreme
## 8 0.0027645 1.88e+02 -0.1925 *** ** Extreme
## 9 1.0000000 1.90e-01 -0.1805 ns ns <NA>
## 10 1.0000000 1.69e-01 -0.6435 ns ns <NA>
## 11 1.0000000 5.27e-02 -0.1805 ns ns <NA>
## 12 1.0000000 8.25e-02 -0.6435 ns ns <NA>
## 13 1.0000000 1.01e-01 0.0000 ns ns <NA>
## 14 1.0000000 7.70e-02 -0.1925 ns ns <NA>
## 15 1.0000000 6.47e-02 -0.6435 ns ns <NA>
## 16 1.0000000 9.99e-02 0.0000 ns ns <NA>
## 17 0.0001374 1.69e+05 -0.6435 *** *** Extreme
## 18 0.7978659 7.41e-01 -0.1925 ns ns <NA>
## 19 1.0000000 2.37e-01 0.1519 ns ns <NA>
## 20 1.0000000 7.44e-02 -0.6435 ns ns <NA>
## 21 0.0004034 5.70e+03 -0.1925 *** *** Extreme
## 22 1.0000000 7.60e-02 0.1519 ns ns <NA>
## 23 0.0091958 6.48e+01 0.4037 *** ** Very Strong
## 24 1.0000000 1.62e-02 -0.6435 ns ns <NA>
## 25 1.0000000 5.27e-01 0.2838 ns ns <NA>
## 26 1.0000000 1.06e-02 -0.1925 ns ns <NA>
## 27 0.5316333 1.29e+00 -0.6435 ns ns Anecdotal
## 28 1.0000000 5.02e-02 0.0000 ns ns <NA>
## 29 1.0000000 7.44e-02 -0.6435 ns ns <NA>
## 30 1.0000000 2.27e-02 -0.6435 ns ns <NA>
## 31 0.0001236 1.14e+04 -0.1925 *** *** Extreme
## 32 1.0000000 6.64e-02 -0.6435 ns ns <NA>
## 33 1.0000000 4.19e-01 -0.6435 ns ns <NA>
## 34 1.0000000 1.41e-02 0.0000 ns ns <NA>
## 35 0.4553413 1.46e+00 -0.1925 * ns Anecdotal
## 36 1.0000000 2.34e-02 -0.1925 ns ns <NA>
## 37 0.0001437 9.70e+04 -0.6435 *** *** Extreme
## 38 1.0000000 6.76e-02 -0.1925 ns ns <NA>
## 39 1.0000000 9.02e-02 -0.1925 ns ns <NA>
## 40 1.0000000 1.85e-02 -0.6435 ns ns <NA>
## 41 1.0000000 1.91e-02 0.0000 ns ns <NA>
## 42 0.0001317 9.07e+04 0.5158 *** *** Extreme
## 43 1.0000000 1.54e-02 -0.6435 ns ns <NA>
## 44 0.2551062 3.21e+00 -0.6435 * ns Moderate
## 45 1.0000000 4.98e-02 0.1519 ns ns <NA>
## 46 1.0000000 1.76e-01 -0.1925 ns ns <NA>
## 47 1.0000000 1.35e-02 -0.6435 ns ns <NA>
## 48 0.3975341 1.94e+00 -0.6435 * ns Anecdotal
## 49 1.0000000 4.98e-02 -0.6435 ns ns <NA>
## 50 1.0000000 9.11e-02 0.0000 ns ns <NA>
## 51 1.0000000 6.34e-02 0.1519 ns ns <NA>
## 52 0.0017623 5.36e+02 -0.6435 *** ** Extreme
## 53 1.0000000 4.97e-02 0.0000 ns ns <NA>
## 54 0.2872346 2.23e+00 -0.6435 * ns Anecdotal
## 55 1.0000000 2.35e-02 0.0000 ns ns <NA>
## 56 0.9836847 5.91e-01 -0.6435 ns ns <NA>
## 57 1.0000000 5.68e-02 0.0173 ns ns <NA>
## 58 0.0011366 1.84e+03 0.0000 *** ** Extreme
## 59 1.0000000 5.30e-02 -0.6435 ns ns <NA>
## 60 1.0000000 2.06e-02 0.2838 ns ns <NA>
## 61 0.0193960 2.66e+01 -0.6435 ** * Strong
## 62 1.0000000 9.32e-03 0.0000 ns ns <NA>
## 63 0.0269388 1.84e+01 -0.1925 ** * Strong
## 64 1.0000000 4.97e-01 -0.6435 ns ns <NA>
## 65 0.0000911 1.48e+07 -0.6435 *** *** Extreme
## 66 1.0000000 8.85e-02 -0.6435 ns ns <NA>
## 67 1.0000000 8.31e-02 0.0000 ns ns <NA>
## 68 1.0000000 5.54e-02 -0.6435 ns ns <NA>
## 69 1.0000000 1.21e-02 0.1519 ns ns <NA>
## 70 1.0000000 6.13e-03 -0.1925 ns ns <NA>
## 71 0.0697778 8.03e+00 -0.1925 ** ns Moderate
## 72 1.0000000 5.33e-03 0.0000 ns ns <NA>
## 73 0.0016848 9.30e+02 -0.6435 *** ** Extreme
## 74 1.0000000 1.35e-01 -0.6435 ns ns <NA>
## 75 0.0000883 1.78e+11 -0.1925 *** *** Extreme
## 76 1.0000000 2.31e-02 -0.1925 ns ns <NA>
## 77 1.0000000 6.37e-02 0.0000 ns ns <NA>
## 78 1.0000000 5.49e-02 0.0000 ns ns <NA>
## 79 1.0000000 1.45e-02 0.0000 ns ns <NA>
## 80 1.0000000 7.96e-03 0.4037 ns ns <NA>chance exp2
## test hatch_condition choice Mean sd n se r p
## 1 FP binocular dark 1L 5.79 5.25 26 1.030 -0.7240 0.999
## 2 FP binocular dark 1R 4.05 5.84 26 1.145 -0.7510 1
## 3 FP binocular dark 2L 7.34 7.65 26 1.501 -0.3990 0.97
## 4 FP binocular dark 2R 5.80 7.62 26 1.493 -0.6010 0.998
## 5 FP binocular dark 3L 9.84 7.67 26 1.505 -0.0352 0.572
## 6 FP binocular dark 3R 8.11 5.88 26 1.154 -0.3330 0.934
## 7 FP binocular dark 4L 18.72 9.25 26 1.813 0.7400 0.000112
## 8 FP binocular dark 4R 19.67 10.02 26 1.966 0.7860 0.000172
## 9 FP binocular dark 5L 8.52 6.81 26 1.336 -0.2060 0.837
## 10 FP binocular dark 5R 12.17 8.74 26 1.715 0.2550 0.139
## 11 FP binocular light 1L 6.55 7.04 26 1.380 -0.4500 0.985
## 12 FP binocular light 1R 4.62 6.31 26 1.238 -0.6860 1
## 13 FP binocular light 2L 9.43 7.65 26 1.501 -0.0792 0.64
## 14 FP binocular light 2R 3.85 4.31 26 0.846 -0.9150 1
## 15 FP binocular light 3L 9.44 7.66 26 1.502 -0.2410 0.857
## 16 FP binocular light 3R 7.72 5.38 26 1.055 -0.5050 0.98
## 17 FP binocular light 4L 21.77 9.89 26 1.939 0.8190 0.000032
## 18 FP binocular light 4R 15.80 9.24 26 1.812 0.6030 0.00243
## 19 FP binocular light 5L 9.83 7.00 26 1.373 -0.0157 0.535
## 20 FP binocular light 5R 10.99 5.68 26 1.115 0.2570 0.144
## 21 FP left dark 1L 23.19 12.97 26 2.543 0.7630 0.0000534
## 22 FP left dark 1R 5.71 7.87 26 1.544 -0.4080 0.982
## 23 FP left dark 2L 16.72 8.62 26 1.690 0.6420 0.000705
## 24 FP left dark 2R 2.22 3.08 26 0.605 -0.8940 1
## 25 FP left dark 3L 12.14 8.09 26 1.586 0.2670 0.108
## 26 FP left dark 3R 5.00 7.24 26 1.419 -0.5940 0.999
## 27 FP left dark 4L 14.84 9.88 26 1.937 0.4730 0.0122
## 28 FP left dark 4R 8.33 6.91 26 1.356 -0.3160 0.928
## 29 FP left dark 5L 6.51 6.35 26 1.245 -0.5300 0.995
## 30 FP left dark 5R 5.34 5.24 26 1.027 -0.7300 1
## 31 FP left light 1L 29.88 12.85 26 2.520 0.8450 8.65e-06
## 32 FP left light 1R 2.25 4.00 26 0.784 -0.8690 1
## 33 FP left light 2L 14.01 8.84 26 1.734 0.4670 0.0131
## 34 FP left light 2R 2.41 3.88 26 0.761 -0.8700 1
## 35 FP left light 3L 12.81 6.86 26 1.345 0.4520 0.0154
## 36 FP left light 3R 3.23 4.45 26 0.873 -0.8340 1
## 37 FP left light 4L 15.01 9.34 26 1.832 0.5180 0.00504
## 38 FP left light 4R 7.94 6.08 26 1.193 -0.3020 0.928
## 39 FP left light 5L 6.42 6.34 26 1.243 -0.4870 0.988
## 40 FP left light 5R 6.04 5.70 26 1.119 -0.5630 0.997
## 41 FP right dark 1L 6.72 8.00 26 1.569 -0.4680 0.991
## 42 FP right dark 1R 33.24 15.74 26 3.086 0.8480 0.0000118
## 43 FP right dark 2L 5.17 7.94 26 1.558 -0.5670 0.997
## 44 FP right dark 2R 12.00 7.26 26 1.425 0.3000 0.0682
## 45 FP right dark 3L 2.84 4.51 26 0.884 -0.8600 1
## 46 FP right dark 3R 10.23 8.04 26 1.577 -0.1080 0.7
## 47 FP right dark 4L 8.29 7.66 26 1.502 -0.2690 0.903
## 48 FP right dark 4R 12.46 9.26 26 1.815 0.2900 0.085
## 49 FP right dark 5L 4.02 5.33 26 1.046 -0.7860 1
## 50 FP right dark 5R 5.04 6.43 26 1.260 -0.6640 1
## 51 FP right light 1L 3.98 5.77 26 1.132 -0.7430 1
## 52 FP right light 1R 28.32 14.71 26 2.885 0.8160 0.0000332
## 53 FP right light 2L 3.02 4.00 26 0.784 -0.8840 1
## 54 FP right light 2R 14.96 9.59 26 1.880 0.5820 0.00191
## 55 FP right light 3L 2.41 2.66 26 0.523 -0.8920 1
## 56 FP right light 3R 10.18 6.69 26 1.311 0.0694 0.396
## 57 FP right light 4L 6.29 6.15 26 1.206 -0.5150 0.993
## 58 FP right light 4R 17.98 9.63 26 1.889 0.7800 0.000135
## 59 FP right light 5L 4.95 5.00 26 0.981 -0.7070 1
## 60 FP right light 5R 7.90 6.35 26 1.245 -0.2980 0.929
## 61 sagittal dark 1 15.66 11.93 26 2.340 0.4780 0.0148
## 62 sagittal dark 10 2.34 4.11 26 0.805 -0.8820 1
## 63 sagittal dark 2 15.05 9.34 26 1.833 0.5490 0.00373
## 64 sagittal dark 3 12.56 10.43 26 2.045 0.2230 0.146
## 65 sagittal dark 4 31.49 15.34 26 3.008 0.8630 0.0000123
## 66 sagittal dark 5 7.17 7.33 26 1.437 -0.3650 0.964
## 67 sagittal dark 6 6.34 6.41 26 1.257 -0.4800 0.99
## 68 sagittal dark 7 3.64 4.57 26 0.896 -0.8440 1
## 69 sagittal dark 8 3.60 4.35 26 0.853 -0.8610 1
## 70 sagittal dark 9 2.16 3.64 26 0.714 -0.8610 1
## 71 sagittal light 1 14.10 9.39 26 1.842 0.4510 0.0141
## 72 sagittal light 10 2.69 5.33 26 1.046 -0.7700 1
## 73 sagittal light 2 13.70 8.42 26 1.651 0.4780 0.0129
## 74 sagittal light 3 13.44 9.66 26 1.895 0.3980 0.0472
## 75 sagittal light 4 32.27 11.23 26 2.203 0.8760 6.29e-06
## 76 sagittal light 5 8.38 5.87 26 1.150 -0.3100 0.915
## 77 sagittal light 6 6.80 4.23 26 0.830 -0.6460 0.999
## 78 sagittal light 7 4.46 4.81 26 0.943 -0.7630 1
## 79 sagittal light 8 1.98 2.56 26 0.501 -0.9020 1
## 80 sagittal light 9 2.17 3.56 26 0.699 -0.9280 1
## p.adj bf ES.h p.sig p.adj.sig bf_cat
## 1 1.0000000 5.11e-02 0.5158 ns ns <NA>
## 2 1.0000000 2.31e-02 0.4037 ns ns <NA>
## 3 1.0000000 8.29e-02 -0.1805 ns ns <NA>
## 4 1.0000000 6.28e-02 -0.1805 ns ns <NA>
## 5 1.0000000 1.91e-01 -0.1925 ns ns <NA>
## 6 1.0000000 8.68e-02 -0.6435 ns ns <NA>
## 7 0.0011240 8.36e+02 0.8503 *** ** Extreme
## 8 0.0017180 1.07e+03 0.0000 *** ** Extreme
## 9 1.0000000 1.08e-01 0.0000 ns ns <NA>
## 10 1.0000000 7.44e-01 0.1519 ns ns <NA>
## 11 1.0000000 6.74e-02 0.1738 ns ns <NA>
## 12 1.0000000 4.96e-02 0.1519 ns ns <NA>
## 13 1.0000000 1.59e-01 0.1519 ns ns <NA>
## 14 1.0000000 1.53e-02 0.2838 ns ns <NA>
## 15 1.0000000 1.60e-01 0.5158 ns ns <NA>
## 16 1.0000000 7.37e-02 0.2838 ns ns <NA>
## 17 0.0003199 1.58e+04 0.0362 *** *** Extreme
## 18 0.0243497 2.19e+01 0.0000 ** * Strong
## 19 1.0000000 1.89e-01 -0.1925 ns ns <NA>
## 20 1.0000000 4.74e-01 0.5158 ns ns <NA>
## 21 0.0005337 2.01e+03 0.5158 *** *** Extreme
## 22 1.0000000 6.33e-02 0.2838 ns ns <NA>
## 23 0.0070519 1.21e+02 0.4338 *** ** Extreme
## 24 1.0000000 7.87e-03 0.2838 ns ns <NA>
## 25 1.0000000 8.37e-01 0.0000 ns ns <NA>
## 26 1.0000000 5.53e-02 -0.1925 ns ns <NA>
## 27 0.1215262 5.34e+00 0.2838 * ns Moderate
## 28 1.0000000 1.02e-01 0.1519 ns ns <NA>
## 29 1.0000000 6.29e-02 0.1519 ns ns <NA>
## 30 1.0000000 4.86e-02 -0.6435 ns ns <NA>
## 31 0.0000865 9.18e+05 -0.6435 *** *** Extreme
## 32 1.0000000 1.06e-02 -0.1925 ns ns <NA>
## 33 0.1314682 3.80e+00 0.4037 * ns Moderate
## 34 1.0000000 1.05e-02 0.6288 ns ns <NA>
## 35 0.1543847 2.58e+00 0.1976 * ns Anecdotal
## 36 1.0000000 1.42e-02 -0.1805 ns ns <NA>
## 37 0.0504484 8.45e+00 0.4037 ** ns Moderate
## 38 1.0000000 8.42e-02 -0.1676 ns ns <NA>
## 39 1.0000000 6.20e-02 0.0000 ns ns <NA>
## 40 1.0000000 5.51e-02 0.6226 ns ns <NA>
## 41 1.0000000 7.52e-02 -0.1925 ns ns <NA>
## 42 0.0001182 4.21e+05 0.0000 *** *** Extreme
## 43 1.0000000 5.94e-02 -0.1925 ns ns <NA>
## 44 0.6818031 9.01e-01 0.4037 ns ns <NA>
## 45 1.0000000 1.35e-02 0.0000 ns ns <NA>
## 46 1.0000000 2.32e-01 -0.6435 ns ns <NA>
## 47 1.0000000 1.06e-01 0.1738 ns ns <NA>
## 48 0.8496833 8.39e-01 0.1519 ns ns <NA>
## 49 1.0000000 2.05e-02 -0.1805 ns ns <NA>
## 50 1.0000000 5.21e-02 0.4037 ns ns <NA>
## 51 1.0000000 2.25e-02 -0.1925 ns ns <NA>
## 52 0.0003315 3.01e+04 -0.1925 *** *** Extreme
## 53 1.0000000 1.20e-02 0.8271 ns ns <NA>
## 54 0.0191143 7.04e+00 -0.1925 ** * Moderate
## 55 1.0000000 6.89e-03 -0.1805 ns ns <NA>
## 56 1.0000000 2.30e-01 -0.6435 ns ns <NA>
## 57 1.0000000 5.96e-02 0.2838 ns ns <NA>
## 58 0.0013493 2.14e+02 0.0000 *** ** Extreme
## 59 1.0000000 2.34e-02 0.1626 ns ns <NA>
## 60 1.0000000 8.54e-02 0.1519 ns ns <NA>
## 61 0.1479105 4.62e+00 0.4037 * ns Moderate
## 62 1.0000000 1.11e-02 0.0000 ns ns <NA>
## 63 0.0372938 8.83e+00 0.3099 ** * Moderate
## 64 1.0000000 7.32e-01 -0.1925 ns ns <NA>
## 65 0.0001226 1.81e+05 0.0000 *** *** Extreme
## 66 1.0000000 7.80e-02 0.4037 ns ns <NA>
## 67 1.0000000 6.16e-02 0.1519 ns ns <NA>
## 68 1.0000000 1.58e-02 0.1519 ns ns <NA>
## 69 1.0000000 1.47e-02 0.3383 ns ns <NA>
## 70 1.0000000 9.41e-03 0.4037 ns ns <NA>
## 71 0.1409965 3.26e+00 -0.1925 * ns Moderate
## 72 1.0000000 1.61e-02 0.4037 ns ns <NA>
## 73 0.1292990 3.37e+00 0.4037 * ns Moderate
## 74 0.4721765 1.65e+00 0.1519 * ns Anecdotal
## 75 0.0000629 8.10e+07 0.0173 *** *** Extreme
## 76 1.0000000 9.46e-02 0.4037 ns ns <NA>
## 77 1.0000000 5.26e-02 0.1519 ns ns <NA>
## 78 1.0000000 1.99e-02 -0.6435 ns ns <NA>
## 79 1.0000000 6.19e-03 0.0000 ns ns <NA>
## 80 1.0000000 9.20e-03 0.1519 ns ns <NA>