[WIP] Continue factor analysis.
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@ -9,6 +9,7 @@ library(conflicted)
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library(here)
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library(tidyverse)
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library(magrittr)
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library(lavaan)
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library(kableExtra)
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conflicts_prefer(
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@ -30,6 +31,7 @@ styler::style_file(
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)
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```
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The data were preprocessed and cleaned using [expl_esm_labels.py](../exploration/expl_esm_labels.py) script and read as csv here.
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```{r read_data}
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COL_TYPES <- cols(
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@ -38,6 +40,7 @@ COL_TYPES <- cols(
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username = col_factor(),
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device_id = col_factor(),
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esm_trigger = col_factor(),
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esm_instructions = col_factor(),
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double_esm_user_answer_timestamp = col_double(),
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datetime_lj = col_datetime(format = ""),
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date_lj = col_date(format = ""),
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@ -47,3 +50,11 @@ COL_TYPES <- cols(
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df_SAM <- read_csv(here("data", "raw", "df_esm_SAM_threat_challenge.csv"), col_types = COL_TYPES)
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df_COPE <- read_csv(here("data", "raw", "df_esm_COPE.csv"), col_types = COL_TYPES)
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```
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Demonstrate factor analysis for a single participant.
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```{r}
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df_COPE %>%
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group_by(question_id, questionnaire_id) %>%
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count()
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```
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