library(tidyverse)
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library(ltm)
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library(dplyr)
library(stats)
library(fastDummies)
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## Thank you for using fastDummies!
## To acknowledge our work, please cite the package:
## Kaplan, J. & Schlegel, B. (2023). fastDummies: Fast Creation of Dummy (Binary) Columns and Rows from Categorical Variables. Version 1.7.1. URL: https://github.com/jacobkap/fastDummies, https://jacobkap.github.io/fastDummies/.
library(knitr)
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library(data.table)
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library(formattable)
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library(DT)
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df_or <- read.csv2("basak_sayisal_veriler.csv")
df <- df_or[-43,]
glimpse(df)
## Rows: 121
## Columns: 146
## $ X <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, …
## $ KOD <int> 75, 31, 54, 3, 70, 104, 87, 7, 37, 82, 81, …
## $ zaman <chr> "2-16-2024 23:24:14", "2-5-2024 14:40", "2-…
## $ kisi_cinsiyet <chr> "Kadin", "Kadin", "Kadin", "Kadin", "Erkek"…
## $ kisi_egitim <chr> "Lisansustu", "Lisans", "Lisans", "Lisans",…
## $ kisi_bolum_poz <chr> "ust yonetim", "Kalite Kontrol-Planlama", "…
## $ kisi_kac_yildir <chr> "10 yildan fazla", "1 yildan 2", "10 yildan…
## $ isletme_sektor <chr> "uretim", "Talasli imalat", "Gida", "Makina…
## $ isletme_isim <chr> "-", "3 Eksen Makina", "Ajinomoto istanbul …
## $ isletme_yabanciOrtak <chr> "Hayir", "Hayir", "Evet", "Evet", "Hayir", …
## $ isletme_yas <chr> "30 yildan fazla", "11 - 30 yil", "30 yilda…
## $ isletme_olcek <chr> "Buyuk", "Orta", "Buyuk", "Orta", "Orta", "…
## $ isletme_cal_say <chr> "250 kisi ve uzeri", "50 - 249 kisi", "50 -…
## $ far_sur_kaynak <int> 5, 4, 5, 5, 4, 4, 4, 5, 4, 3, 5, 5, 5, 5, 3…
## $ far_sur_gelecek <int> 5, 2, 5, 4, 4, 3, 3, 4, 4, 4, 5, 5, 5, 5, 3…
## $ far_sur_adil_is <int> 5, 3, 5, 5, 5, 4, 5, 4, 5, 4, 5, 5, 5, 5, 5…
## $ far_sur_toplum <int> 4, 2, 5, 5, 4, 4, 5, 4, 5, 3, 5, 5, 4, 5, 4…
## $ far_sur_cevre_koruma <int> 4, 3, 5, 4, 4, 3, 5, 4, 5, 4, 5, 5, 5, 5, 5…
## $ far_sur_paydas <int> 4, 3, 5, 5, 5, 3, 4, 5, 4, 3, 5, 5, 5, 5, 4…
## $ far_sur_eko_performans <int> 4, 5, 5, 5, 4, 4, 5, 5, 4, 3, 5, 5, 5, 5, 4…
## $ far_sur_calisan_hak <int> 5, 2, 5, 4, 5, 4, 3, 5, 3, 2, 5, 5, 5, 5, 5…
## $ far_sur_tarim <int> 1, 1, 5, 3, 3, 1, 4, 3, 5, 4, 4, 5, 5, 3, 4…
## $ far_cev_karbon <int> 5, 1, 3, 3, 4, 3, 4, 5, 3, 4, 5, 3, 4, 4, 3…
## $ far_cev_atik <int> 5, 3, 5, 3, 5, 3, 5, 5, 3, 4, 5, 4, 3, 5, 3…
## $ far_cev_enerji <int> 4, 3, 5, 5, 4, 3, 5, 4, 4, 4, 5, 3, 3, 4, 4…
## $ far_cev_su <int> 3, 2, 5, 3, 3, 3, 5, 4, 4, 4, 5, 3, 3, 4, 3…
## $ far_cev_iklim <int> 4, 1, 4, 2, 3, 3, 3, 4, 2, 3, 5, 3, 4, 4, 3…
## $ far_sos_egitim <int> 3, 2, 5, 2, 4, 2, 5, 4, 4, 2, 4, 4, 4, 5, 3…
## $ far_sos_cinsiyet <int> 3, 3, 5, 2, 3, 2, 3, 5, 3, 2, 4, 4, 4, 4, 5…
## $ far_sos_is_sagligi <int> 5, 3, 5, 4, 4, 3, 5, 5, 4, 4, 4, 5, 5, 5, 5…
## $ far_sos_tedarikci <int> 3, 1, 5, 2, 4, 1, 5, 4, 4, 3, 3, 5, 5, 3, 3…
## $ far_sos_sorumluluk <int> 4, 1, 5, 2, 3, 2, 5, 4, 3, 3, 5, 5, 5, 4, 3…
## $ far_sos_calisan <int> 4, 1, 5, 4, 4, 3, 5, 4, 3, 2, 5, 5, 5, 5, 5…
## $ far_sos_musteri <int> 5, 5, 5, 4, 5, 4, 5, 5, 4, 4, 5, 5, 5, 5, 5…
## $ far_sos_sosyal_hak <int> 3, 4, 5, 4, 4, 3, 3, 4, 4, 4, 3, 5, 4, 4, 5…
## $ far_sos_yetenek <int> 4, 4, 5, 4, 4, 4, 5, 4, 4, 2, 4, 5, 4, 4, 4…
## $ far_sos_istihdam <int> 4, 2, 5, 4, 5, 4, 5, 5, 5, 3, 5, 4, 4, 4, 3…
## $ far_sos_urun_guvenlik <int> 3, 2, 5, 4, 5, 5, 5, 5, 4, 3, 5, 5, 5, 4, 4…
## $ far_sos_inovasyon <int> 2, 2, 5, 4, 4, 5, 5, 5, 4, 3, 5, 5, 5, 3, 3…
## $ far_sos_motivasyon <int> 4, 3, 5, 4, 3, 3, 4, 4, 4, 2, 5, 5, 5, 4, 5…
## $ far_sos_kirilgan <int> 3, 2, 5, 3, 3, 2, 4, 3, 2, 2, 5, 5, 4, 3, 4…
## $ far_yon_belge <int> 5, 3, 5, 4, 5, 5, 4, 5, 4, 4, 4, 4, 5, 3, 4…
## $ far_yon_kultur <int> 3, 2, 5, 4, 4, 4, 5, 4, 4, 3, 4, 4, 4, 4, 4…
## $ far_yon_mevzuat <int> 5, 4, 5, 5, 5, 4, 5, 5, 4, 4, 4, 5, 5, 4, 5…
## $ far_yon_cevre_politika <int> 5, 3, 5, 3, 4, 3, 5, 5, 4, 4, 4, 5, 5, 5, 4…
## $ far_yon_sur_hedef <int> 3, 1, 5, 4, 4, 4, 5, 5, 5, 3, 5, 5, 5, 4, 4…
## $ far_eko_verimlilik <int> 5, 4, 5, 4, 4, 3, 4, 5, 3, 3, 4, 5, 5, 4, 4…
## $ far_eko_satin_alma <int> 3, 2, 5, 3, 3, 4, 3, 4, 3, 3, 4, 5, 5, 3, 3…
## $ far_eko_teknoloji <int> 4, 1, 5, 4, 4, 4, 4, 5, 3, 3, 4, 5, 5, 3, 3…
## $ far_birim_sur <int> 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0…
## $ far_birim_cevre <int> 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1…
## $ far_birim_isg <int> 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1…
## $ far_birim_kalite <int> 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1…
## $ far_birim_idari <int> 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1…
## $ far_birim_satin_alma <int> 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1…
## $ far_birim_finans <int> 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1…
## $ far_birim_pazarlama <int> 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1…
## $ far_birim_muhasebe <int> 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1…
## $ far_birim_ik <int> 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1…
## $ far_birim_iletisim <int> 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0…
## $ far_birim_lojistik <int> 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1…
## $ far_birim_depolama <int> 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1…
## $ far_itici_yonetim <int> 4, 1, 4, 4, 4, 4, 4, 4, 3, 3, 5, 5, 4, 5, 3…
## $ far_itici_mutakabat <int> 5, 1, 4, 3, 5, 2, 4, 4, 3, 3, 5, 4, 5, 1, 2…
## $ far_itici_oneri <int> 2, 3, 4, 3, 4, 2, 3, 4, 4, 3, 3, 5, 5, 4, 4…
## $ far_itici_duzeltici <int> 2, 4, 5, 3, 4, 3, 5, 4, 3, 3, 3, 5, 5, 4, 4…
## $ far_itici_sertifikasyon <int> 3, 4, 5, 4, 5, 4, 5, 5, 3, 4, 3, 4, 2, 5, 4…
## $ far_itici_ortaklik <int> 4, 3, 4, 4, 5, 2, 4, 5, 2, 4, 5, 1, 3, 1, 3…
## $ far_itici_sur_hedef <int> 3, 2, 5, 3, 4, 3, 4, 5, 3, 3, 4, 4, 5, 3, 2…
## $ far_itici_musteri <int> 5, 5, 4, 4, 4, 4, 2, 5, 2, 4, 5, 5, 4, 5, 4…
## $ far_itici_stk <int> 4, 1, 4, 3, 4, 3, 2, 3, 3, 3, 5, 5, 3, 3, 3…
## $ far_itici_verimlilik <int> 5, 1, 5, 3, 4, 3, 5, 5, 3, 3, 5, 5, 5, 1, 3…
## $ far_itici_mevzuat <int> 4, 3, 4, 4, 5, 4, 5, 4, 2, 4, 5, 5, 4, 5, 3…
## $ far_itici_merak <int> 3, 1, 5, 3, 5, 4, 4, 4, 3, 3, 2, 5, 2, 3, 3…
## $ far_engel_veri <int> 2, 4, 3, 5, 3, 2, 2, 2, 3, 4, 2, 4, 4, 4, 3…
## $ far_engel_maliyet <int> 4, 5, 4, 3, 3, 4, 5, 3, 4, 5, 2, 4, 5, 4, 5…
## $ far_engel_2_personel <int> 5, 5, 3, 5, 5, 5, 3, 3, 3, 3, 2, 4, 4, 5, 4…
## $ far_engel_direnc <int> 5, 5, 2, 3, 3, 4, 5, 2, 3, 5, 3, 5, 3, 4, 4…
## $ far_engel_kar <int> 4, 5, 2, 3, 3, 3, 5, 2, 4, 4, 1, 4, 5, 4, 5…
## $ far_engel_iletisim <int> 4, 5, 1, 4, 2, 3, 2, 1, 3, 5, 1, 5, 3, 3, 4…
## $ far_arac_iso14001 <int> 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1…
## $ far_arac_iso45001 <int> 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1…
## $ far_arac_iso9001 <int> 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1…
## $ far_arac_iso50001 <int> 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1…
## $ far_arac_iso27001 <int> 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0…
## $ far_arac_ohsas18001 <int> 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0…
## $ far_arac_brc <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ far_arac_iatf16949 <int> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1…
## $ far_arac_global_compact <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ far_arac_diger <int> 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0…
## $ far_cev_fay_enerji <int> 3, 3, 4, 5, 5, 2, 3, 5, 4, 3, 5, 5, 5, 4, 5…
## $ far_cev_fay_atik <int> 3, 4, 5, 3, 4, 3, 5, 5, 3, 3, 5, 5, 5, 4, 5…
## $ far_cev_fay_emisyon <int> 3, 4, 4, 3, 3, 2, 2, 4, 3, 3, 4, 5, 5, 4, 3…
## $ far_cev_fay_su <int> 3, 2, 4, 3, 4, 2, 3, 4, 4, 3, 5, 5, 5, 4, 5…
## $ far_sos_fay_nitelikli <int> 4, 2, 5, 4, 3, 5, 5, 4, 4, 3, 4, 5, 2, 4, 5…
## $ far_sos_fay_guvenli <int> 4, 2, 5, 4, 4, 3, 5, 5, 4, 3, 5, 5, 5, 4, 5…
## $ far_sos_fay_toplum_refah <int> 4, 1, 5, 4, 5, 2, 5, 4, 5, 3, 5, 5, 4, 4, 5…
## $ far_sos_fay_esit_calisma <int> 4, 1, 5, 4, 4, 2, 4, 4, 5, 3, 5, 5, 4, 4, 5…
## $ far_sos_fay_rekabet <int> 2, 3, 5, 4, 3, 4, 3, 5, 4, 3, 4, 5, 4, 4, 5…
## $ far_sos_fay_calisan_refah <int> 4, 1, 5, 4, 4, 3, 3, 4, 3, 3, 5, 5, 4, 4, 5…
## $ far_yon_yesil <int> 2, 1, 4, 3, 3, 3, 3, 4, 4, 2, 5, 4, 5, 3, 3…
## $ far_yon_marka <int> 2, 2, 5, 4, 3, 4, 5, 4, 5, 2, 5, 5, 5, 4, 5…
## $ far_eko_maliyet <int> 5, 4, 4, 4, 2, 4, 3, 4, 4, 3, 4, 5, 5, 3, 5…
## $ far_eko_karlilik <int> 5, 5, 4, 4, 2, 5, 3, 4, 4, 3, 4, 5, 4, 3, 5…
## $ far_pay_tedarikci <int> 3, 4, 4, 3, 3, 2, 2, 3, 4, 2, 3, 5, 4, 3, 5…
## $ far_pay_bilinc <int> 3, 4, 5, 3, 4, 3, 3, 4, 4, 2, 5, 5, 5, 4, 5…
## $ far_pay_top_fayda <int> 3, 1, 5, 4, 5, 2, 4, 4, 5, 2, 5, 5, 5, 3, 5…
## $ far_pay_musteri <int> 3, 5, 4, 4, 3, 3, 5, 4, 5, 2, 3, 5, 5, 4, 5…
## $ far_pay_ulke_ekonomi <int> 3, 2, 4, 4, 5, 3, 5, 4, 5, 2, 3, 5, 5, 4, 5…
## $ far_pay_cev_sagligi <int> 4, 1, 4, 3, 4, 2, 5, 4, 4, 2, 4, 5, 5, 5, 5…
## $ far_pay_dongu_ekonomi <int> 3, 2, 4, 4, 4, 4, 4, 4, 4, 2, 4, 5, 5, 4, 5…
## $ far_pay_yatirimci <int> 1, 4, 4, 4, 3, 2, 2, 4, 4, 2, 3, 5, 4, 5, 5…
## $ far_pay_etik <int> 3, 2, 5, 3, 5, 3, 5, 4, 5, 2, 3, 5, 5, 5, 5…
## $ far_pay_engelli <int> 3, 1, 5, 3, 3, 2, 2, 3, 4, 2, 5, 5, 4, 4, 5…
## $ far_pay_insan_haklari <int> 5, 2, 5, 3, 4, 3, 4, 4, 5, 2, 5, 5, 4, 5, 5…
## $ far_pay_diger_isletme <int> 3, 2, 5, 4, 4, 4, 5, 4, 4, 2, 5, 5, 5, 4, 5…
## $ Yon_plan_ust_yonetim <int> 3, 4, 5, 4, 4, 4, 3, 5, 4, 2, 5, 5, 4, 5, 5…
## $ Yon_plan_amac <int> 3, 2, 5, 4, 4, 4, 3, 5, 4, 2, 5, 5, 5, 5, 5…
## $ Yon_plan_stratejik_plan <int> 3, 2, 4, 4, 5, 4, 3, 5, 5, 2, 5, 5, 5, 5, 5…
## $ Yon_plan_risk_analiz <int> 4, 1, 4, 4, 4, 3, 3, 5, 4, 2, 5, 5, 5, 5, 5…
## $ Yon_plan_eylem_plan <int> 3, 2, 4, 4, 4, 3, 3, 5, 4, 2, 5, 5, 4, 5, 5…
## $ Yon_plan_kaynak <int> 3, 3, 4, 4, 5, 4, 3, 5, 5, 2, 5, 5, 4, 4, 5…
## $ Yon_plan_oncelik <int> 2, 1, 4, 3, 4, 3, 3, 5, 5, 2, 5, 5, 4, 4, 5…
## $ Yon_plan_kalkinma_amac <int> 4, 1, 4, 3, 4, 3, 3, 5, 5, 2, 5, 5, 4, 4, 5…
## $ Yon_uyg_veri <int> 3, 1, 4, 3, 3, 3, 4, 5, 4, 3, 4, 5, 4, 4, 4…
## $ Yon_uyg_birim <int> 3, 2, 4, 3, 3, 3, 4, 5, 4, 3, 4, 5, 5, 4, 4…
## $ Yon_uyg_teknolojik <int> 3, 1, 4, 3, 4, 4, 5, 5, 4, 3, 4, 5, 5, 4, 4…
## $ Yon_uyg_egitim <int> 4, 2, 4, 3, 4, 4, 4, 4, 4, 3, 4, 5, 5, 4, 5…
## $ Yon_uyg_yetkinlik <int> 2, 1, 5, 3, 5, 3, 4, 5, 5, 3, 4, 5, 4, 4, 5…
## $ Yon_uyg_motivasyon <int> 2, 1, 5, 3, 5, 3, 3, 4, 5, 3, 5, 5, 3, 3, 5…
## $ Yon_uyg_calisan_baglilik <int> 4, 1, 5, 4, 4, 2, 2, 4, 5, 3, 4, 5, 3, 3, 5…
## $ Yon_uyg_adil_is <int> 4, 1, 5, 3, 5, 3, 2, 4, 4, 3, 4, 5, 4, 3, 5…
## $ Yon_uyg_firsat_esitlik <int> 5, 1, 5, 3, 5, 3, 3, 4, 4, 3, 4, 5, 5, 3, 5…
## $ Yon_ilet_internet <int> 1, 1, 5, 1, 2, 2, 3, 4, 4, 2, 4, 5, 4, 1, 5…
## $ Yon_ilet_pano <int> 4, 1, 5, 2, 5, 2, 3, 4, 4, 2, 4, 5, 4, 2, 5…
## $ Yon_ilet_kulup <int> 1, 1, 4, 1, 3, 2, 2, 5, 5, 1, 5, 5, 4, 2, 5…
## $ Yon_ilet_birim <int> 1, 1, 4, 3, 4, 3, 5, 5, 4, 1, 5, 5, 5, 3, 5…
## $ Yon_ilet_rapor <int> 1, 1, 4, 4, 4, 1, 3, 5, 5, 1, 5, 5, 4, 4, 5…
## $ Yon_kont_tedarikci <int> 3, 2, 4, 3, 3, 3, 4, 4, 3, 2, 4, 5, 3, 3, 5…
## $ Yon_kont_gozden_gecirme <int> 4, 2, 5, 4, 4, 3, 5, 4, 3, 2, 4, 5, 4, 3, 5…
## $ Yon_kont_sertifika <int> 3, 3, 5, 4, 4, 4, 4, 5, 3, 2, 4, 5, 4, 4, 5…
## $ Yon_kont_surec_hedef <int> 3, 2, 5, 4, 5, 3, 4, 4, 2, 2, 4, 5, 4, 4, 5…
## $ Yon_kont_bilim_temelli <int> 4, 2, 4, 4, 4, 3, 5, 4, 2, 2, 4, 5, 4, 4, 5…
## $ Yon_iyiles_hafiza <int> 3, 1, 5, 4, 5, 4, 4, 4, 5, 2, 5, 5, 5, 3, 5…
## $ Yon_iyiles_calisan_gorus <int> 4, 4, 5, 3, 5, 3, 3, 4, 4, 2, 5, 5, 5, 4, 5…
## $ Yon_iyiles_duzeltici_rapor <int> 4, 3, 5, 4, 4, 3, 3, 4, 5, 2, 5, 5, 4, 4, 5…
extract_factors <- function (df,what,howmany,reduce=0,rotat="promax"){
cat("________________ START --> ", what, "_____________________")
cat("\n")
center <- function(x) { return (x - mean(x))}
df_sub <- df %>% dplyr::select(starts_with(what)) %>% mutate(across(everything(), center))
CA <- round(cronbach.alpha(df_sub) $ alpha,2)
cat("\n")
cat("cronbach_alpa =", CA)
cat("\n")
if (reduce != 0) df_sub=df_sub[,-reduce]
FA<- df_sub%>%factanal(.,howmany, scores ="regression",rotation=rotat)
print(FA $ loadings)
explained <- 1-FA $ uniquenesses
barplot(explained,cex.names=0.7, col=1:length(explained),
main="faktor analizining acikladigi oranlar", cex.main=0.8)
cat("\n")
cat("faktor analizining acikladigi oranlar:");cat("\n")
explained_props <- as.data.frame(1-FA $ uniquenesses)
colnames(explained_props) ="explained_variances"
print(explained_props);cat("\n")
cat("likelihood ratio test | p-value:", FA $ PVAL); cat("\n")
if(FA $ PVAL<0.05) print("factors are not sufficient")
else cat("\n", "factors are sufficient")
cat("\n")
cat("________________ END _____________________")
outcome <-list(FA,df_sub)
return(outcome)
}
dummy_func <- function (df,this_X,this_key) {
dummy <- list()
for (a in 1:length(this_X)) {
dummy[[a]] <- df %>%
dplyr::select(starts_with(this_key)) %>%
dplyr::select(c(this_X[a])) %>%
dummy_cols %>%
dplyr::select(where(is.numeric)) %>%
dplyr::select(c(-1)) }
dummies_as_df <- do.call(data.frame,dummy)
return(dummies_as_df)
}
show_model_details <- function(model_now){
cat("\n")
model_now %>%
cooks.distance %>%
plot(.,type="h",col="black",
main=paste(model_now $call[2],"cooks distances (verilerin modele etkileri)"), cex.main = 0.6);abline(h=1,lty=2,col="red")
cat(rep("##",3),sep="")
paste("Y =", model_now $call[2]) %>% print
cat(rep("##",3),sep="")
cat("\n")
model_now %>% summary %>% print
}
make_model <- function(df,Y_df,dummies,this_key){
df_pilot <- cbind(Y_df,dummies)
model_sosyal_cevresel_boyut <- lm(df_pilot $sosyal_cevresel_donusum~.,data = df_pilot[,-c(2)])
model_sosyal_cevresel_boyut%>%show_model_details
model_verimlilik_boyutu <- lm(df_pilot $ verimlilik_boyutu~.,data = df_pilot [,-c(1)])
model_verimlilik_boyutu%>%show_model_details}
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>% names
## [1] "isletme_sektor" "isletme_isim" "isletme_yabanciOrtak"
## [4] "isletme_yas" "isletme_olcek" "isletme_cal_say"
## [7] "kisi_cinsiyet" "kisi_egitim" "kisi_bolum_poz"
## [10] "kisi_kac_yildir"
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(3)) %>%
table
## isletme_yabanciOrtak
## Evet Hayir
## 51 70
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(5,6)) %>% table
## isletme_cal_say
## isletme_olcek 10 - 49 kisi 250 kisi ve uzeri 50 - 249 kisi
## Buyuk 1 36 11
## Kucuk 9 0 6
## Orta 9 9 40
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(4)) %>% table
## isletme_yas
## 1 - 10 yil 11 - 30 yil 30 yildan fazla
## 15 51 55
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(7)) %>% table
## kisi_cinsiyet
## Belirtmek istemiyorum Erkek Kadin
## 2 74 45
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(8)) %>% table
## kisi_egitim
## Doktora Lisans Lisansustu Lise Yuksekokul
## 2 78 37 1 3
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(9)) %>% datatable
df %>%
dplyr::select(starts_with("isletme") | starts_with("kisi")) %>%
dplyr::select(c(10)) %>% table
## kisi_kac_yildir
## 1 - 5 yil
## 35
## 1 yildan 2
## 6
## 10 yildan fazla
## 44
## 20 yildir ayni sektordeyim. Bunun 12 yili fabrikada Ar-ge bolumunde, 8 senesi ise satis-p2arlama bolumunde gecti
## 1
## 6 - 10 yil
## 35
see_sur <- extract_factors(df,"far_sur",2,reduce=9)
## ________________ START --> far_sur _____________________
##
## cronbach_alpa = 0.92
##
## Loadings:
## Factor1 Factor2
## far_sur_kaynak -0.108 1.083
## far_sur_gelecek 0.494 0.395
## far_sur_adil_is 0.835
## far_sur_toplum 0.961 -0.177
## far_sur_cevre_koruma 0.852
## far_sur_paydas 0.511 0.303
## far_sur_eko_performans 0.213 0.457
## far_sur_calisan_hak 0.791
##
## Factor1 Factor2
## SS loadings 3.533 1.669
## Proportion Var 0.442 0.209
## Cumulative Var 0.442 0.650
##
## faktor analizining acikladigi oranlar:
## explained_variances
## far_sur_kaynak 0.9950000
## far_sur_gelecek 0.7166284
## far_sur_adil_is 0.7116268
## far_sur_toplum 0.6778400
## far_sur_cevre_koruma 0.7547568
## far_sur_paydas 0.6042706
## far_sur_eko_performans 0.4127530
## far_sur_calisan_hak 0.7388179
##
## likelihood ratio test | p-value: 0.01026063
## [1] "factors are not sufficient"
##
## ________________ END _____________________
see_sur_scores <- see_sur[[1]] $ scores
colnames(see_sur_scores) <- c("sosyal_cevresel_donusum","verimlilik_boyutu")
see_sur_scores %>% boxplot(.,horizontal=TRUE,cex.axis=0.7,
col=1:dim(see_sur_scores)[2],
main = "Faktor analizinin turettigi bagimli degiskenler", cex.main=0.7)
du_df <- dummy_func(df,c(3),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.0941 -1.0758 0.3579 0.9630 4.4524
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.3941 0.2139 -1.843 0.0679 .
## isletme_yabanciOrtak_Hayir 0.6812 0.2812 2.423 0.0169 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.527 on 119 degrees of freedom
## Multiple R-squared: 0.047, Adjusted R-squared: 0.039
## F-statistic: 5.869 on 1 and 119 DF, p-value: 0.01691
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6561 -0.4851 0.0714 0.8327 3.4998
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3219 0.2238 1.438 0.153
## isletme_yabanciOrtak_Hayir -0.5564 0.2942 -1.891 0.061 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.598 on 119 degrees of freedom
## Multiple R-squared: 0.02918, Adjusted R-squared: 0.02102
## F-statistic: 3.577 on 1 and 119 DF, p-value: 0.06102
du_df <- dummy_func(df,c(4),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5408 -1.0804 0.4742 0.9113 5.0058
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3716 0.4008 0.927 0.356
## isletme_yas_11...30.yil -0.6378 0.4560 -1.399 0.165
## isletme_yas_30.yildan.fazla -0.2260 0.4522 -0.500 0.618
##
## Residual standard error: 1.552 on 118 degrees of freedom
## Multiple R-squared: 0.02353, Adjusted R-squared: 0.006976
## F-statistic: 1.422 on 2 and 118 DF, p-value: 0.2454
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.0861 -0.3586 -0.0502 0.9788 3.0698
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.8411 0.4120 -2.042 0.0434 *
## isletme_yas_11...30.yil 1.0365 0.4686 2.212 0.0289 *
## isletme_yas_30.yildan.fazla 0.8892 0.4648 1.913 0.0581 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.596 on 118 degrees of freedom
## Multiple R-squared: 0.04052, Adjusted R-squared: 0.02426
## F-statistic: 2.492 on 2 and 118 DF, p-value: 0.0871
du_df <- dummy_func(df,c(3,4),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.8425 -1.0062 0.5022 0.9343 4.7041
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.01475 0.42076 0.035 0.9721
## isletme_yabanciOrtak_Hayir 0.66902 0.28109 2.380 0.0189 *
## isletme_yas_11...30.yil -0.64832 0.44726 -1.450 0.1499
## isletme_yas_30.yildan.fazla -0.28277 0.44417 -0.637 0.5256
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.523 on 117 degrees of freedom
## Multiple R-squared: 0.06862, Adjusted R-squared: 0.04474
## F-statistic: 2.873 on 3 and 117 DF, p-value: 0.03926
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.8279 -0.6729 0.0073 1.1049 3.3280
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.5357 0.4356 -1.230 0.2212
## isletme_yabanciOrtak_Hayir -0.5725 0.2910 -1.967 0.0515 .
## isletme_yas_11...30.yil 1.0455 0.4631 2.258 0.0258 *
## isletme_yas_30.yildan.fazla 0.9378 0.4599 2.039 0.0437 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.576 on 117 degrees of freedom
## Multiple R-squared: 0.07124, Adjusted R-squared: 0.04743
## F-statistic: 2.992 on 3 and 117 DF, p-value: 0.03381
du_df <- dummy_func(df,c(5),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.7229 -1.0290 0.5457 0.9661 4.8237
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.01706 0.22575 -0.076 0.940
## isletme_olcek_Kucuk 0.39705 0.46265 0.858 0.393
## isletme_olcek_Orta -0.06710 0.30518 -0.220 0.826
##
## Residual standard error: 1.564 on 118 degrees of freedom
## Multiple R-squared: 0.008895, Adjusted R-squared: -0.007903
## F-statistic: 0.5295 on 2 and 118 DF, p-value: 0.5903
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.7498 -0.4232 0.0536 0.9181 3.0156
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2600 0.2330 1.116 0.267
## isletme_olcek_Kucuk -0.5475 0.4775 -1.147 0.254
## isletme_olcek_Orta -0.4009 0.3150 -1.273 0.206
##
## Residual standard error: 1.614 on 118 degrees of freedom
## Multiple R-squared: 0.018, Adjusted R-squared: 0.001357
## F-statistic: 1.082 on 2 and 118 DF, p-value: 0.3424
du_df <- dummy_func(df,c(3,4,5),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.7292 -1.0210 0.4287 1.0269 4.8174
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.003176 0.509000 -0.006 0.9950
## isletme_yabanciOrtak_Hayir 0.648314 0.287143 2.258 0.0258 *
## isletme_yas_11...30.yil -0.597607 0.468956 -1.274 0.2051
## isletme_yas_30.yildan.fazla -0.197125 0.491643 -0.401 0.6892
## isletme_olcek_Kucuk 0.239602 0.504788 0.475 0.6359
## isletme_olcek_Orta -0.125377 0.305806 -0.410 0.6826
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.531 on 115 degrees of freedom
## Multiple R-squared: 0.07397, Adjusted R-squared: 0.03371
## F-statistic: 1.837 on 5 and 115 DF, p-value: 0.111
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.7128 -0.6827 0.0147 1.0043 3.1791
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.3576 0.5269 -0.679 0.4986
## isletme_yabanciOrtak_Hayir -0.5574 0.2972 -1.875 0.0633 .
## isletme_yas_11...30.yil 1.0011 0.4854 2.062 0.0414 *
## isletme_yas_30.yildan.fazla 0.8772 0.5089 1.724 0.0875 .
## isletme_olcek_Kucuk -0.1135 0.5225 -0.217 0.8284
## isletme_olcek_Orta -0.2640 0.3165 -0.834 0.4061
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.585 on 115 degrees of freedom
## Multiple R-squared: 0.07697, Adjusted R-squared: 0.03684
## F-statistic: 1.918 on 5 and 115 DF, p-value: 0.09662
du_df <- dummy_func(df,c(6),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.7805 -0.9798 0.3903 0.9755 4.7660
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2166 0.3597 0.602 0.548
## isletme_cal_say_50...249.kisi -0.2431 0.4154 -0.585 0.559
## isletme_cal_say_250.kisi.ve.uzeri -0.2746 0.4290 -0.640 0.523
##
## Residual standard error: 1.568 on 118 degrees of freedom
## Multiple R-squared: 0.003718, Adjusted R-squared: -0.01317
## F-statistic: 0.2202 on 2 and 118 DF, p-value: 0.8027
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.7895 -0.3402 -0.0317 0.9473 3.0882
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.11585 0.37234 -0.311 0.756
## isletme_cal_say_50...249.kisi 0.01472 0.42994 0.034 0.973
## isletme_cal_say_250.kisi.ve.uzeri 0.29287 0.44404 0.660 0.511
##
## Residual standard error: 1.623 on 118 degrees of freedom
## Multiple R-squared: 0.00718, Adjusted R-squared: -0.009647
## F-statistic: 0.4267 on 2 and 118 DF, p-value: 0.6537
du_df <- dummy_func(df,c(3,4,6),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.9139 -0.9227 0.4386 1.0160 4.6326
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.03536 0.47340 -0.075 0.9406
## isletme_yabanciOrtak_Hayir 0.68796 0.28894 2.381 0.0189 *
## isletme_yas_11...30.yil -0.64571 0.49996 -1.292 0.1991
## isletme_yas_30.yildan.fazla -0.24225 0.51898 -0.467 0.6415
## isletme_cal_say_50...249.kisi 0.10003 0.45210 0.221 0.8253
## isletme_cal_say_250.kisi.ve.uzeri -0.07390 0.48827 -0.151 0.8800
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.534 on 115 degrees of freedom
## Multiple R-squared: 0.07106, Adjusted R-squared: 0.03068
## F-statistic: 1.76 on 5 and 115 DF, p-value: 0.1267
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6425 -0.6196 0.0849 1.1257 3.2376
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.2607 0.4868 -0.536 0.5933
## isletme_yabanciOrtak_Hayir -0.6520 0.2971 -2.194 0.0302 *
## isletme_yas_11...30.yil 1.2462 0.5142 2.424 0.0169 *
## isletme_yas_30.yildan.fazla 1.1008 0.5337 2.062 0.0414 *
## isletme_cal_say_50...249.kisi -0.5816 0.4649 -1.251 0.2135
## isletme_cal_say_250.kisi.ve.uzeri -0.3058 0.5021 -0.609 0.5437
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.577 on 115 degrees of freedom
## Multiple R-squared: 0.0861, Adjusted R-squared: 0.04637
## F-statistic: 2.167 on 5 and 115 DF, p-value: 0.06253
du_df <- dummy_func(df,c(3,4,5,6),"isletme")
make_model(df,Y_df=see_sur_scores,
dummies= du_df,
this_key="isletme")
## ######[1] "Y = df_pilot$sosyal_cevresel_donusum ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$sosyal_cevresel_donusum ~ ., data = df_pilot[,
## -c(2)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.803 -1.017 0.238 1.012 4.743
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.02987 0.61985 0.048 0.9616
## isletme_yabanciOrtak_Hayir 0.70053 0.29519 2.373 0.0193 *
## isletme_yas_11...30.yil -0.64166 0.50409 -1.273 0.2057
## isletme_yas_30.yildan.fazla -0.18932 0.52933 -0.358 0.7213
## isletme_olcek_Kucuk 0.11055 0.59441 0.186 0.8528
## isletme_olcek_Orta -0.29405 0.38125 -0.771 0.4422
## isletme_cal_say_50...249.kisi 0.20170 0.47921 0.421 0.6746
## isletme_cal_say_250.kisi.ve.uzeri -0.12478 0.57964 -0.215 0.8299
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.54 on 113 degrees of freedom
## Multiple R-squared: 0.08022, Adjusted R-squared: 0.02324
## F-statistic: 1.408 on 7 and 113 DF, p-value: 0.209
## ######[1] "Y = df_pilot$verimlilik_boyutu ~ ."
## ######
##
## Call:
## lm(formula = df_pilot$verimlilik_boyutu ~ ., data = df_pilot[,
## -c(1)])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6151 -0.6473 0.1124 1.0658 3.1730
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.01257 0.63939 -0.020 0.9844
## isletme_yabanciOrtak_Hayir -0.61694 0.30450 -2.026 0.0451 *
## isletme_yas_11...30.yil 1.22057 0.51997 2.347 0.0206 *
## isletme_yas_30.yildan.fazla 1.07324 0.54601 1.966 0.0518 .
## isletme_olcek_Kucuk -0.29856 0.61315 -0.487 0.6272
## isletme_olcek_Orta -0.25051 0.39327 -0.637 0.5254
## isletme_cal_say_50...249.kisi -0.61609 0.49431 -1.246 0.2152
## isletme_cal_say_250.kisi.ve.uzeri -0.49879 0.59791 -0.834 0.4059
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.588 on 113 degrees of freedom
## Multiple R-squared: 0.08959, Adjusted R-squared: 0.0332
## F-statistic: 1.589 on 7 and 113 DF, p-value: 0.1459