A codebook contains documentation and metadata describing the contents, structure, and layout of a data file.
The data contains 401 cases and 43 variables.
| name | type | n | missing | unique | mean | median | mode | sd | min | max | range | skew | skew_2se | kurt | kurt_2se |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| sepa_soc_1 | numeric | 353 | 0.12 | 6 | 3.54 | 4.00 | 4.00 | 0.99 | 1.0 | 5.0 | 4.0 | -0.63 | -2.41 | -0.03 | -0.05 |
| sepa_soc_2 | numeric | 353 | 0.12 | 6 | 1.95 | 2.00 | 2.00 | 0.87 | 1.0 | 5.0 | 4.0 | 0.88 | 3.38 | 0.67 | 1.30 |
| sepa_soc_3 | numeric | 353 | 0.12 | 6 | 2.67 | 3.00 | 3.00 | 1.14 | 1.0 | 5.0 | 4.0 | 0.31 | 1.20 | -0.75 | -1.45 |
| sepa_soc_4 | numeric | 353 | 0.12 | 6 | 2.10 | 2.00 | 2.00 | 1.04 | 1.0 | 5.0 | 4.0 | 0.68 | 2.63 | -0.34 | -0.65 |
| sepa_soc_5 | numeric | 353 | 0.12 | 6 | 1.88 | 2.00 | 2.00 | 0.99 | 1.0 | 5.0 | 4.0 | 1.03 | 3.97 | 0.31 | 0.61 |
| sepa_eco_1 | numeric | 353 | 0.12 | 6 | 3.29 | 4.00 | 4.00 | 1.13 | 1.0 | 5.0 | 4.0 | -0.28 | -1.07 | -0.88 | -1.70 |
| sepa_eco_2 | numeric | 353 | 0.12 | 6 | 2.98 | 3.00 | 3.00 | 1.14 | 1.0 | 5.0 | 4.0 | 0.07 | 0.26 | -0.96 | -1.84 |
| sepa_eco_3 | numeric | 353 | 0.12 | 6 | 2.74 | 3.00 | 3.00 | 1.06 | 1.0 | 5.0 | 4.0 | 0.26 | 1.00 | -0.69 | -1.34 |
| sepa_eco_4 | numeric | 353 | 0.12 | 6 | 3.38 | 4.00 | 4.00 | 1.03 | 1.0 | 5.0 | 4.0 | -0.59 | -2.28 | -0.36 | -0.70 |
| sepa_eco_5 | numeric | 353 | 0.12 | 6 | 3.57 | 4.00 | 4.00 | 0.94 | 1.0 | 5.0 | 4.0 | -0.69 | -2.64 | -0.02 | -0.04 |
| secs_soc_1 | numeric | 349 | 0.13 | 63 | 3.53 | 3.00 | 3.00 | 2.39 | 1.0 | 11.0 | 10.0 | 1.04 | 3.98 | 0.80 | 1.53 |
| secs_soc_2 | numeric | 349 | 0.13 | 80 | 6.10 | 6.20 | 6.20 | 2.20 | 0.0 | 10.0 | 10.0 | -0.53 | -2.04 | 0.21 | 0.41 |
| secs_soc_3 | numeric | 349 | 0.13 | 79 | 4.43 | 5.00 | 5.00 | 2.24 | 0.0 | 10.0 | 10.0 | 0.05 | 0.21 | 0.11 | 0.22 |
| secs_soc_4 | numeric | 348 | 0.13 | 84 | 4.28 | 5.00 | 5.00 | 2.74 | 0.0 | 10.0 | 10.0 | -0.04 | -0.15 | -0.89 | -1.70 |
| secs_soc_5 | numeric | 349 | 0.13 | 81 | 4.37 | 5.00 | 5.00 | 2.41 | 0.0 | 10.0 | 10.0 | -0.09 | -0.33 | -0.57 | -1.10 |
| secs_soc_6 | numeric | 348 | 0.13 | 80 | 6.80 | 7.00 | 7.00 | 2.34 | 0.0 | 10.0 | 10.0 | -0.63 | -2.41 | -0.06 | -0.11 |
| secs_soc_7 | numeric | 349 | 0.13 | 80 | 3.64 | 4.00 | 4.00 | 2.45 | 0.0 | 10.0 | 10.0 | 0.22 | 0.83 | -0.65 | -1.24 |
| secs_eco_1 | numeric | 349 | 0.13 | 72 | 4.82 | 5.00 | 5.00 | 1.83 | 0.0 | 10.0 | 10.0 | -0.14 | -0.54 | 0.65 | 1.25 |
| secs_eco_2 | numeric | 348 | 0.13 | 67 | 3.87 | 3.90 | 3.90 | 1.85 | 1.0 | 10.9 | 9.9 | 0.50 | 1.92 | 0.45 | 0.86 |
| secs_eco_3 | numeric | 346 | 0.14 | 48 | 1.16 | 0.50 | 0.50 | 1.72 | 0.0 | 10.0 | 10.0 | 2.19 | 8.34 | 5.16 | 9.87 |
| secs_eco_4 | numeric | 349 | 0.13 | 71 | 5.68 | 5.40 | 5.40 | 1.77 | 0.0 | 10.0 | 10.0 | -0.24 | -0.92 | 1.03 | 1.98 |
| secs_eco_5 | numeric | 349 | 0.13 | 77 | 5.72 | 5.70 | 5.70 | 1.97 | 0.1 | 10.0 | 9.9 | -0.43 | -1.63 | 0.40 | 0.77 |
| fam_1 | numeric | 350 | 0.13 | 80 | 5.24 | 5.60 | 5.60 | 2.53 | 0.0 | 10.0 | 10.0 | -0.25 | -0.94 | -0.63 | -1.22 |
| fam_2 | numeric | 350 | 0.13 | 91 | 4.76 | 5.00 | 5.00 | 2.59 | 0.0 | 10.0 | 10.0 | -0.06 | -0.23 | -0.86 | -1.66 |
| fam_3 | numeric | 350 | 0.13 | 87 | 3.79 | 4.00 | 4.00 | 2.45 | 0.0 | 10.0 | 10.0 | 0.19 | 0.72 | -0.82 | -1.57 |
| grp_1 | numeric | 350 | 0.13 | 81 | 4.37 | 5.00 | 5.00 | 2.17 | 0.0 | 10.0 | 10.0 | -0.28 | -1.06 | -0.71 | -1.36 |
| grp_2 | numeric | 351 | 0.12 | 82 | 4.48 | 4.80 | 4.80 | 2.30 | 0.0 | 10.0 | 10.0 | 0.00 | 0.00 | -0.68 | -1.31 |
| grp_3 | numeric | 351 | 0.12 | 85 | 5.76 | 6.10 | 6.10 | 2.40 | 0.0 | 10.0 | 10.0 | -0.51 | -1.97 | -0.28 | -0.53 |
| rec_1 | numeric | 350 | 0.13 | 79 | 5.47 | 5.90 | 5.90 | 2.19 | 0.0 | 10.0 | 10.0 | -0.52 | -1.99 | 0.01 | 0.01 |
| rec_2 | numeric | 351 | 0.12 | 78 | 6.73 | 7.00 | 7.00 | 2.03 | 0.0 | 10.0 | 10.0 | -0.71 | -2.74 | 0.43 | 0.83 |
| rec_3 | numeric | 351 | 0.12 | 77 | 6.55 | 7.00 | 7.00 | 2.13 | 0.0 | 10.0 | 10.0 | -0.81 | -3.10 | 0.59 | 1.13 |
| her_1 | numeric | 351 | 0.12 | 87 | 5.86 | 6.00 | 6.00 | 2.24 | 0.0 | 10.0 | 10.0 | -0.39 | -1.51 | -0.22 | -0.43 |
| her_2 | numeric | 351 | 0.12 | 88 | 4.51 | 5.00 | 5.00 | 2.43 | 0.0 | 10.0 | 10.0 | 0.08 | 0.30 | -0.58 | -1.12 |
| her_3 | numeric | 350 | 0.13 | 84 | 3.61 | 3.00 | 3.00 | 3.02 | 0.0 | 10.0 | 10.0 | 0.45 | 1.71 | -1.00 | -1.93 |
| def_1 | numeric | 350 | 0.13 | 78 | 3.23 | 3.10 | 3.10 | 2.21 | 0.0 | 10.0 | 10.0 | 0.33 | 1.27 | -0.60 | -1.15 |
| def_2 | numeric | 350 | 0.13 | 87 | 4.46 | 5.00 | 5.00 | 2.47 | 0.0 | 10.0 | 10.0 | -0.23 | -0.87 | -0.78 | -1.50 |
| def_3 | numeric | 351 | 0.12 | 87 | 5.19 | 5.30 | 5.30 | 2.74 | 0.0 | 10.0 | 10.0 | -0.26 | -0.99 | -0.78 | -1.51 |
| fai_1 | numeric | 351 | 0.12 | 73 | 7.73 | 8.30 | 8.30 | 2.33 | 0.0 | 10.0 | 10.0 | -1.26 | -4.84 | 1.27 | 2.45 |
| fai_2 | numeric | 351 | 0.12 | 58 | 8.81 | 9.50 | 9.50 | 1.59 | 2.0 | 10.0 | 8.0 | -1.66 | -6.39 | 2.76 | 5.32 |
| fai_3 | numeric | 351 | 0.12 | 77 | 7.11 | 7.50 | 7.50 | 2.54 | 0.0 | 10.0 | 10.0 | -0.81 | -3.10 | 0.04 | 0.07 |
| pro_1 | numeric | 351 | 0.12 | 92 | 5.78 | 5.60 | 5.60 | 2.70 | 1.0 | 11.0 | 10.0 | 0.13 | 0.49 | -0.81 | -1.55 |
| pro_2 | numeric | 350 | 0.13 | 70 | 9.10 | 9.90 | 9.90 | 2.05 | 1.0 | 11.0 | 10.0 | -1.46 | -5.58 | 2.11 | 4.05 |
| pro_3 | numeric | 350 | 0.13 | 70 | 8.54 | 9.15 | 9.15 | 2.23 | 1.0 | 11.0 | 10.0 | -0.87 | -3.33 | 0.12 | 0.22 |
- Name: Variable name
- type: Data type of the variable
- missing: Proportion of missing values for this variable
- unique: Number of unique values
- mean: Mean value
- median: Median value
- mode: Most common value (for categorical variables, this shows the frequency of the most common category)
- mode_value: For categorical variables, the value of the most common category
- sd: Standard deviation (measure of dispersion for numerical variables
- v: Agresti’s V (measure of dispersion for categorical variables)
- min: Minimum value
- max: Maximum value
- range: Range between minimum and maximum value
- skew: Skewness of the variable
- skew_2se: Skewness of the variable divided by 2*SE of the skewness. If this is greater than abs(1), skewness is significant
- kurt: Kurtosis (peakedness) of the variable
- kurt_2se: Kurtosis of the variable divided by 2*SE of the kurtosis. If this is greater than abs(1), kurtosis is significant.
This codebook was generated using the Workflow for Open Reproducible Code in Science (WORCS)