Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = My outcome variable
---Overview---
outcome_variable_name outcome_variable_level cases n P P_LL
1 My outcome variable Affected 8 22 0.3636364 0.1976126
2 My outcome variable Not Affected 14 22 0.6363636 0.4283818
P_UL P_SE P_adjusted ta_LL ta_UL
1 0.5716182 0.09541133 0.3846154 0.2276777 0.5415531
2 0.8023874 0.09541133 0.6153846 0.4584469 0.7723223
-- es_proportion_difference --
outcome_variable_name case_label effect
1 My outcome variable P_ Affected My outcome variable
2 My outcome variable P_ Affected Reference value
3 My outcome variable P_ Affected My outcome variable ‒ Reference value
effect_size LL UL SE effect_size_adjusted ta_LL
1 0.3636364 0.1976126 0.57161816 0.09541133 0.3846154 0.2276777
2 0.5000000 NA NA NA NA NA
3 -0.1363636 -0.3023874 0.07161816 0.09541133 -0.1153846 -0.2723223
ta_UL cases n type
1 0.54155306 8 22 Comparison
2 NA 8 22 Reference
3 0.04155306 8 22 Difference
Note: LL and UL are lower and upper boundaries of confidence intervals with 95% expected coverage.
Code
estimate
Output
Analysis of raw data:
Outcome variable(s) = dep_status
---Overview---
outcome_variable_name outcome_variable_level cases n P P_LL
1 dep_status Depressed 8 22 0.3636364 0.1388521
2 dep_status NotDepressed 14 22 0.6363636 0.3696213
3 dep_status Missing 3 NA NA NA
P_UL P_SE P_adjusted ta_LL ta_UL
1 0.6303787 0.09541133 0.3846154 0.1626554 0.6065753
2 0.8611479 0.09541133 0.6153846 0.3934247 0.8373446
3 NA NA NA NA NA
-- es_proportion_difference --
outcome_variable_name case_label effect effect_size
1 dep_status P_ Depressed dep_status 0.3636364
2 dep_status P_ Depressed Reference value 0.0000000
3 dep_status P_ Depressed dep_status ‒ Reference value 0.3636364
LL UL SE effect_size_adjusted ta_LL ta_UL cases
1 0.1388521 0.6303787 0.09541133 0.3846154 0.1626554 0.6065753 8
2 NA NA NA NA NA NA 8
3 0.1388521 0.6303787 0.09541133 0.3846154 0.1626554 0.6065753 8
n type
1 22 Comparison
2 22 Reference
3 22 Difference
[1] "Missing values were present; these were *not* counted as part of the total sample size."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
Code
estimate
Output
Analysis of raw data:
Data frame = data
Outcome variable(s) = depression_status
---Overview---
outcome_variable_name outcome_variable_level cases n P P_LL
1 depression_status Depressed 8 22 0.3636364 0.1388521
2 depression_status NotDepressed 14 22 0.6363636 0.3696213
3 depression_status Missing 3 NA NA NA
P_UL P_SE P_adjusted ta_LL ta_UL
1 0.6303787 0.09541133 0.3846154 0.1626554 0.6065753
2 0.8611479 0.09541133 0.6153846 0.3934247 0.8373446
3 NA NA NA NA NA
-- es_proportion_difference --
outcome_variable_name case_label effect
1 depression_status P_ Depressed depression_status
2 depression_status P_ Depressed Reference value
3 depression_status P_ Depressed depression_status ‒ Reference value
effect_size LL UL SE effect_size_adjusted ta_LL
1 0.3636364 0.1388521 0.6303787 0.09541133 0.3846154 0.1626554
2 0.0000000 NA NA NA NA NA
3 0.3636364 0.1388521 0.6303787 0.09541133 0.3846154 0.1626554
ta_UL cases n type
1 0.6065753 8 22 Comparison
2 NA 8 22 Reference
3 0.6065753 8 22 Difference
[1] "Missing values were present; these were *not* counted as part of the total sample size."
Note: LL and UL are lower and upper boundaries of confidence intervals with 99% expected coverage.
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