AnalysesPreliminary regression analyses indicated that neither the mai translation - AnalysesPreliminary regression analyses indicated that neither the mai Indonesian how to say

AnalysesPreliminary regression anal

Analyses
Preliminary regression analyses indicated that neither the main effect for
rater gender,   .02, p  .62, nor the interaction between rater gender
and ratee gender,   .06, p  .67, was significantly related to performance
ratings so we combined the data for all raters in subsequent
analyses. Similarly, a preliminary logistic regression analysis indicated that
neither the main effect for rater gender, b  .21, p  .60, nor the
interaction between rater gender and ratee gender, b  .46, p  .58, was
significantly related to promotion decisions so we also combined those data
for all raters.
We tested Hypothesis 1 by carrying out a linear regression analysis with
the nine-dimension composite performance scale as the dependent variable,
and controls for human capital (age, organizational tenure, education, and
organizational level) in Step 1; gender in Step 2 (to see if there was a
significant main effect); job type in Step 3; and the gender by job type
interaction in Step 4. We then conducted three planned orthogonal contrasts,
as suggested by Strube and Bobko (1989) for testing an ordinal
interaction when it is predicted that differences are due to one cell, as in our
case where we predicted that women in line jobs would receive lower
performance ratings than the other three groups. To control for study-wise
error, we set the significance level for each of the three contrasts at  
.05/3  .017.
We tested Hypothesis 2 with a linear regression analysis predicting
composite performance ratings, with control variables and the main effects
for job type in Step 1, and gender in Step 2, and we carried out an
exploratory analysis of initial job type as a moderating variable by entering
the gender by initial job type interaction in Step 3. We limited the sample
for these analyses to the 77 managers who had received promotions. For all
regression analyses we used simultaneous entry of all variables within each
step, and significance of the results was determined from the significance
of beta coefficients and change statistics.
Finally, we tested Hypothesis 3 with a logistic regression analysis
because promotion was a dichotomous variable. We entered the previously
used control variables and job type as an additional control variable
(because promotional opportunities might vary in line and staff positions)
in Step 1, gender in Step 2 (to see if there was a significant main effect),
performance rating in Step 3, and the interaction of gender and performance
rating in Step 4. We carried out an exploratory analysis of initial job
type as a moderating variable by entering the additional two-way interactions
in Step 5; and the three-way interaction of gender, performance
ratings, and initial job type in Step 6. We centered the composite performance
ratings in the logistic regression analyses to eliminate unnecessary
multicollinearity between this variable and the interaction term (Cohen,
Cohen, West, & Aiken, 2003). Then we conducted separate logistic regression
analyses for female managers and male managers. Because some
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Results (Indonesian) 1: [Copy]
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AnalysesPreliminary regression analyses indicated that neither the main effect forrater gender,   .02, p  .62, nor the interaction between rater genderand ratee gender,   .06, p  .67, was significantly related to performanceratings so we combined the data for all raters in subsequentanalyses. Similarly, a preliminary logistic regression analysis indicated thatneither the main effect for rater gender, b  .21, p  .60, nor theinteraction between rater gender and ratee gender, b  .46, p  .58, wassignificantly related to promotion decisions so we also combined those datafor all raters.We tested Hypothesis 1 by carrying out a linear regression analysis withthe nine-dimension composite performance scale as the dependent variable,and controls for human capital (age, organizational tenure, education, andorganizational level) in Step 1; gender in Step 2 (to see if there was asignificant main effect); job type in Step 3; and the gender by job typeinteraction in Step 4. We then conducted three planned orthogonal contrasts,as suggested by Strube and Bobko (1989) for testing an ordinalinteraction when it is predicted that differences are due to one cell, as in ourcase where we predicted that women in line jobs would receive lowerperformance ratings than the other three groups. To control for study-wiseerror, we set the significance level for each of the three contrasts at  .05/3  .017.We tested Hypothesis 2 with a linear regression analysis predictingcomposite performance ratings, with control variables and the main effectsfor job type in Step 1, and gender in Step 2, and we carried out anexploratory analysis of initial job type as a moderating variable by enteringthe gender by initial job type interaction in Step 3. We limited the samplefor these analyses to the 77 managers who had received promotions. For allregression analyses we used simultaneous entry of all variables within eachstep, and significance of the results was determined from the significanceof beta coefficients and change statistics.Finally, we tested Hypothesis 3 with a logistic regression analysisbecause promotion was a dichotomous variable. We entered the previouslyused control variables and job type as an additional control variable(because promotional opportunities might vary in line and staff positions)in Step 1, gender in Step 2 (to see if there was a significant main effect),performance rating in Step 3, and the interaction of gender and performancerating in Step 4. We carried out an exploratory analysis of initial jobtype as a moderating variable by entering the additional two-way interactionsin Step 5; and the three-way interaction of gender, performanceratings, and initial job type in Step 6. We centered the composite performanceratings in the logistic regression analyses to eliminate unnecessarymulticollinearity between this variable and the interaction term (Cohen,Cohen, West, & Aiken, 2003). Then we conducted separate logistic regressionanalyses for female managers and male managers. Because some
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Results (Indonesian) 2:[Copy]
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Analisis
analisis regresi awal menunjukkan bahwa baik efek utama untuk
penilai jenis kelamin,? ? ? .02, P? 0,62, maupun interaksi antara penilai jender
dan ratee jenis kelamin,? ? ? 0,06, p? 0,67, secara signifikan berhubungan dengan kinerja
peringkat sehingga kami menggabungkan data untuk semua penilai di berikutnya
analisis. Demikian pula, analisis regresi logistik pendahuluan menunjukkan bahwa
tidak efek utama untuk penilai jenis kelamin, b? 0,21, p? 0,60, maupun
interaksi antara penilai gender dan ratee jender, b? 0,46, p? 0,58, itu
secara signifikan terkait dengan keputusan promosi sehingga kami juga menggabungkan data mereka
untuk semua penilai.
Kami menguji hipotesis 1 dengan melakukan analisis regresi linear dengan
skala sembilan dimensi komposit kinerja sebagai variabel dependen,
dan kontrol untuk modal manusia (usia , masa organisasi, pendidikan, dan
tingkat organisasi) pada Langkah 1; gender dalam Langkah 2 (untuk melihat apakah ada
efek utama yang signifikan); Jenis pekerjaan di Langkah 3; dan gender dengan jenis pekerjaan
interaksi pada Langkah 4. Kami kemudian dilakukan tiga kontras orthogonal direncanakan,
seperti yang disarankan oleh Strube dan Bobko (1989) untuk menguji sebuah ordinal
interaksi ketika diperkirakan bahwa perbedaan adalah karena satu sel, seperti dalam kita
kasus di mana kami memperkirakan bahwa perempuan dalam pekerjaan baris akan menerima lebih rendah
peringkat kinerja dari tiga kelompok lainnya. Untuk mengontrol untuk studi-bijaksana
kesalahan, kita mengatur tingkat signifikansi untuk masing-masing tiga kontras di? ?
05/3? 0,017.
Kami menguji hipotesis 2 dengan analisis regresi linear memprediksi
peringkat kinerja komposit, dengan variabel kontrol dan efek utama
untuk jenis pekerjaan pada Langkah 1, dan jenis kelamin pada Langkah 2, dan kami melakukan sebuah
analisis eksplorasi jenis pekerjaan awal sebagai variabel moderasi dengan memasukkan
jenis kelamin dengan interaksi jenis pekerjaan awal pada Langkah 3. Kami terbatas sampel
untuk analisis ini ke 77 manajer yang telah menerima promosi. Untuk semua
analisis regresi kami menggunakan entri simultan dari semua variabel dalam setiap
langkah, dan signifikansi dari hasil ditentukan dari signifikansi
dari koefisien beta dan statistik perubahan.
Akhirnya, kami menguji Hipotesis 3 dengan analisis regresi logistik
karena promosi adalah variabel dikotomis. Kami memasuki sebelumnya
digunakan variabel kontrol dan jenis pekerjaan sebagai variabel kontrol tambahan
(karena kesempatan promosi mungkin bervariasi sejalan dan staf posisi)
pada Langkah 1, gender dalam Langkah 2 (untuk melihat apakah ada efek utama yang signifikan),
peringkat kinerja di Langkah 3, dan interaksi gender dan kinerja
wisatawan pada Langkah 4. Kami melakukan analisis eksplorasi pekerjaan awal
tipe sebagai variabel moderasi dengan memasukkan interaksi dua arah tambahan
di langkah 5; dan interaksi tiga arah gender, kinerja
peringkat, dan jenis pekerjaan awal pada Langkah 6. Kami berpusat kinerja komposit
peringkat di analisis regresi logistik untuk menghilangkan yang tidak perlu
multikolinearitas antara variabel ini dan istilah interaksi (Cohen,
Cohen, Barat, & Aiken, 2003). Kemudian kami melakukan regresi logistik terpisah
analisis bagi manajer perempuan dan laki-laki manajer. karena beberapa
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