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stress_at_work_analysis
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Add an old script to test JCQ reversal.

master
junos 2023-07-03 14:23:55 +02:00
parent db06584ddd
commit 7b0c0037f7
5 changed files with 248 additions and 1 deletions
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10
.idea/misc.xml
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@ -17,7 +17,15 @@
</RMarkdownRenderProfile>
</value>
</entry>
<entry key="file://$PROJECT_DIR$/statistical_analysis/scale_reliability.rmd">
<value>
<RMarkdownRenderProfile>
<option name="lastOutput" value="$PROJECT_DIR$/statistical_analysis/scale_reliability.nb.html" />
<option name="outputDirectoryUrl" value="file://$PROJECT_DIR$/statistical_analysis" />
</RMarkdownRenderProfile>
</value>
</entry>
</map>
</option>
</component>
</project>
</project>

9
.idea/rGraphicsSettings.xml 100644
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@ -0,0 +1,9 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="RGraphicsSettings">
<option name="height" value="600" />
<option name="resolution" value="75" />
<option name="version" value="2" />
<option name="width" value="960" />
</component>
</project>

7
.idea/rMarkdownGraphicsSettings.xml 100644
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@ -0,0 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="RMarkdownGraphicsSettings">
<option name="globalResolution" value="75" />
<option name="version" value="2" />
</component>
</project>

6
.idea/rSettings.xml 100644
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@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="RSettings">
<option name="interpreterPath" value="C:\Program Files\R\R-4.3.1\bin\R.exe" />
</component>
</project>

217
exploration/test_JCQ_reversal.py 100644
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@ -0,0 +1,217 @@
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.14.5
# kernelspec:
# display_name: straw2analysis
# language: python
# name: straw2analysis
# ---
# %%
import pandas as pd
from features.esm_JCQ import dict_JCQ_demand_control_reverse
# %%
limesurvey_questions = pd.read_csv(
"E:/STRAWbaseline/survey637813+question_text.csv", header=None
).T
# %%
limesurvey_questions
# %%
limesurvey_questions[["code", "text"]] = limesurvey_questions[0].str.split(
r"\.\s", expand=True, n=1
)
# %%
limesurvey_questions
# %%
demand_reverse_lime_rows = (
limesurvey_questions["text"].str.startswith(" [Od mene se ne zahteva,")
| limesurvey_questions["text"].str.startswith(" [Imam dovolj časa, da končam")
| limesurvey_questions["text"].str.startswith(
" [Pri svojem delu se ne srečujem s konfliktnimi"
)
)
control_reverse_lime_rows = limesurvey_questions["text"].str.startswith(
" [Moje delo vključuje veliko ponavljajočega"
) | limesurvey_questions["text"].str.startswith(
" [Pri svojem delu imam zelo malo svobode"
)
# %%
demand_reverse_lime = limesurvey_questions[demand_reverse_lime_rows]
demand_reverse_lime.loc[:, "qid"] = demand_reverse_lime["code"].str.extract(
r"\[(\d+)\]"
)
control_reverse_lime = limesurvey_questions[control_reverse_lime_rows]
control_reverse_lime.loc[:, "qid"] = control_reverse_lime["code"].str.extract(
r"\[(\d+)\]"
)
# %%
limesurvey_questions.loc[89, "text"]
# %%
limesurvey_questions[limesurvey_questions["code"].str.startswith("JobEisen")]
# %%
demand_reverse_lime
# %%
control_reverse_lime
# %%
participant_info = pd.read_csv(
"C:/Users/junos/Documents/FWO-ARRS/Analysis/straw2analysis/rapids/data/raw/p031/participant_baseline_raw.csv",
parse_dates=["date_of_birth"],
)
# %%
participant_info_t = participant_info.T
# %%
rows_baseline = participant_info_t.index
# %%
rows_demand = rows_baseline.str.startswith("JobEisen") & ~rows_baseline.str.endswith(
"Time"
)
# %%
rows_baseline[rows_demand]
# %%
limesurvey_control = (
participant_info_t[rows_demand]
.reset_index()
.rename(columns={"index": "question", 0: "score_original"})
)
# %%
limesurvey_control
# %%
limesurvey_control["qid"] = (
limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
)
# %%
limesurvey_control["question"].str.extract(r"\[(\d+)\]").astype(int)
# %%
limesurvey_control["score"] = limesurvey_control["score_original"]
# %%
limesurvey_control["qid"][0]
# %%
rows_demand_reverse = limesurvey_control["qid"].isin(
dict_JCQ_demand_control_reverse.keys()
)
limesurvey_control.loc[rows_demand_reverse, "score"] = (
4 + 1 - limesurvey_control.loc[rows_demand_reverse, "score_original"]
)
# %%
JCQ_DEMAND = "JobEisen"
JCQ_CONTROL = "JobControle"
dict_JCQ_demand_control_reverse = {
JCQ_DEMAND: {
3: " [Od mene se ne zahteva,",
4: " [Imam dovolj časa, da končam",
5: " [Pri svojem delu se ne srečujem s konfliktnimi",
},
JCQ_CONTROL: {
2: " |Moje delo vključuje veliko ponavljajočega",
6: " [Pri svojem delu imam zelo malo svobode",
},
}
# %%
limesurvey_control
# %%
test = pd.DataFrame(
data={"question": "one", "score_original": 3, "score": 3, "qid": 10}, index=[0]
)
# %%
pd.concat([test, limesurvey_control]).reset_index()
# %%
limesurvey_control["score"].sum()
# %%
rows_demand_reverse
# %%
dict_JCQ_demand_control_reverse[JCQ_DEMAND].keys()
# %%
limesurvey_control
# %%
DEMAND_CONTROL_RATIO_MIN = 5 / (9 * 4)
DEMAND_CONTROL_RATIO_MAX = (4 * 5) / 9
JCQ_NORMS = {
"F": {
0: DEMAND_CONTROL_RATIO_MIN,
1: 0.45,
2: 0.52,
3: 0.62,
4: DEMAND_CONTROL_RATIO_MAX,
},
"M": {
0: DEMAND_CONTROL_RATIO_MIN,
1: 0.41,
2: 0.48,
3: 0.56,
4: DEMAND_CONTROL_RATIO_MAX,
},
}
# %%
JCQ_NORMS[participant_info.loc[0, "gender"]][0]
# %%
participant_info_t.index.str.startswith("JobControle")
# %%
columns_baseline = participant_info.columns
# %%
columns_demand = columns_baseline.str.startswith(
"JobControle"
) & ~columns_baseline.str.endswith("Time")
# %%
columns_baseline[columns_demand]
# %%
participant_control = participant_info.loc[:, columns_demand]
# %%
participant_control["id"] = participant_control.index
# %%
participant_control
# %%
pd.wide_to_long(
participant_control,
stubnames="JobControle",
i="id",
j="qid",
sep="[",
suffix="(\\d+)]",
)