The Importance of Absorption Capacity and Innovation in Improving Company Performance

The purpose of this research is to analyze the importance of absorption capacity and innovation in improving company performance. The research method used in this study is a quantitative method with a descriptive analysis approach. The research population is all manufacturing companies which are included in the theoretical domain and listed on the Indonesia Stock Exchange. In this study, ten manufacturing companies listed on the Indonesia Stock Exchange were selected. For the company's performance variable, the Return on Assets (ROA) indicator is used. The type of data used in this study is secondary data. The analysis technique in this study is the outer model (convergent validity, discriminant validity and composite reliability). Based on the data and research results, it can be concluded that: 1) Absorption Capacity has an effect on Company Performance with a positive and significant influence on company performance which is indicated by the original sample estimate value of 0.922 and the T-statistic value of 11.777 which is greater than the t-value. table (1.96); and 2) Company innovation has no effect on Company Performance with the original sample estimate value of -0.23 and the T-statistic value of 0.297 which is smaller than the t-table value (1.96).

Dependence Types in a Binarized Precipitation Network

<p>In a network of binarized precipitation (i.e., wet or dry value), the connection or dependence between each pair of nodes can occur following one or more of the following conditions: wet‐wet, dry‐dry, wet‐dry, or dry‐wet. Here, we firstly investigate the different types of dependence, year by year, within a precipitation network of binarized variables. We compare the sample estimate of the probability of co‐occurrence (or occurrence with a lag time within ±3 days) of each of the four possible combinations with respect to the correspondent confidence interval in hypothesis of independence. We develop a procedure to efficiently assess the dependence behavior of all couples of nodes within the network and apply the methodology to a network of rain gauges covering Europe and north Africa.</p>

The Effect of Transformation Leadership on Organizational Performance through the Strong Lecturer Engagement

Transformational leadership is one of the leadership types that can be applied in an organization, especially for organizations in the field of education. This study was conducted on several lecturers spread across several campuses in Indonesia. The research method uses SEM- {PLS). The results showed as follows. (1) Engagement influences performance with a T-statistic value of 4.000 (> 1.96). Furthermore, the original sample estimate value is positive that is 0.582. Therefore, H1 is accepted. (2) There is a significant relationship between transformational leadership and engagement with a T-statistic value of 16.737 (> 1.96). Furthermore, the original sample estimate value is positive that is 0.820. Therefore, H2 is accepted. (3) There is no significant relationship between the transformational leadership and performance with a T- statistic value of 0.145 (< 1.96). Furthermore, the original sample estimate value is positive that 0.202 which indicates that the relationship between transformational leadership and performance is negative. Therefore, H3 is rejected.

Reflections on modern methods: demystifying robust standard errors for epidemiologists

All statistical estimates from data have uncertainty due to sampling variability. A standard error is one measure of uncertainty of a sample estimate (such as the mean of a set of observations or a regression coefficient). Standard errors are usually calculated based on assumptions underpinning the statistical model used in the estimation. However, there are situations in which some assumptions of the statistical model including the variance or covariance of the outcome across observations are violated, which leads to biased standard errors. One simple remedy is to userobust standard errors, which are robust to violations of certain assumptions of the statistical model. Robust standard errors are frequently used in clinical papers (e.g. to account for clustering of observations), although the underlying concepts behind robust standard errors and when to use them are often not well understood. In this paper, we demystify robust standard errors using several worked examples in simple situations in which model assumptions involving the variance or covariance of the outcome are misspecified. These are: (i) when the observed variances are different, (ii) when the variance specified in the model is wrong and (iii) when the assumption of independence is wrong.

Sample Size Determination in Survey Research

Obtaining a representative sample size remains critical to survey researchers because of its implication for cost, time and precision of the sample estimate. However, the difficulty of obtaining a good estimate of population variance coupled with insufficient skills in sampling theory impede the researchers’ ability to obtain an optimum sample in survey research. This paper proposes an adjustment to the margin of error in Yamane’s (1967) formula to make it applicable for use in determining optimum sample size for both continuous and categorical variables at all levels of confidence. A minimum sample size determination table is developed for use by researchers based on the adjusted formula developed in this paper.

Validity of Marital Conflict Resolution Scale Using Reflective Measurement Model of PLS-SEM

This research describes the validity of marital conflict resolution scale that formulated from Gottman theory about marital conflict resolution. Marital conflict resolution scale presented to 255 married women in Makassar city. Consisting of 26 items, marital conflict resolution scale there are two dimensions consisting of constructive resolution and destructive resolution. Constructive resolution consist 11 items and destructive resolution consist 15 items has had five choices of the answer. The answer ranging from strongly agree (1 score) to strongly disagree (5 score) for favorable item, and unfavorable items get the opposite score. Validity of marital conflict resolution scale is tested using the reflective measurement model of PLS-SEM. The results of the outer model and the structure or inner model have shown the original sample estimate ≥ 0.50, this means that each indicators can represent both dimensions.AbstrakPenelitian ini menguraikan mengenai validitas skala penyelesaian konflik perkawinan yang dirumuskan dari teori Gottman tentang penyelesaian konflik perkawinan. Skala penyelesaian konflik perkawinan diberikan kepada 255 responden wanita menikah di kota Makassar. Terdiri dari 26 item, skala penyelesaian konflik perkawinan memiliki dua dimensi yang terdiri dari penyelesaian konstruktif dan penyelesaian destruktif. Penyelesaian konstruktif terdiri dari 11 item dan penyelesaian destruktif terdiri dari 15 item memiliki lima pilihan jawaban. Jawaban mulai dari sangat setuju (1 skor) hingga sangat tidak setuju (5 skor) untuk item yang menguntungkan, dan item yang tidak menguntungkan mendapatkan skor yang berlawanan. Validitas skala penyelesaian konflik pernikahan diuji menggunakan model pengukuran reflektif PLS-SEM. Hasil outer model dan struktur atau inner model menunjukkan original sample estimate ≥ 0,50, ini berarti bahwa masing-masing indikator dapat mewakili kedua dimensi.

Pengaruh Kepemimpinan terhadap Disiplin Kerja Pegawai Kantor Kementerian Agama Kota Bukittinggi dengan Motivasi Kerja Sebagai Variabel Moderating

The results showed that the influence between leadership and work discipline was significant. The influence between leadership and work motivation was also significant. The influence between work motivation cannot strengthen the leadership relationship to Work Discipline and is not significant. with a T-statistic of 1,2572541846236 (<1,960). The original sample estimate value is negative, amounting to -0.13494828, which shows that the direction of the relationship between Leadership and Work Discipline which is moderated by motivational variables has a negative and insignificant effect, while the influence between leadership and work discipline at the Office of the Ministry of Religion in Bukittinggi has a positive influence. and significant, so does the influence of leadership on motivation has a positive and significant influence and finally the influence of motivation on work discipline at the Office of the Ministry of Religion in Bukittinggi has a positive and significant effect so that all hypotheses submitted can be accepted except the leadership hypothesis in moderation of work motivation variables working discipline at the Bukittinggi City Ministry of Religion's Office is unacceptable. Keywords: Leadership, Motivation and Discipline

2850. Burden of Difficult-to-Treat Antibiotic-Resistant (DTR) Gram-Negative Infections in the United States, 2012–2017

Background Difficult-to-treat resistance (DTR) is a metric for clinically relevant “pan-resistance” to available high-efficacy, low-toxicity antibiotic treatment options at any given time. Previous DTR prevalence estimates in Gram-negative (GN) bloodstream isolates from 2009 to 2014 have ranged between 1 and 1.5%. We sought to estimate the national burden of DTR GN isolates and more recent trends by region, site, and species. Methods Clinical cultures with GN isolates were identified from inpatient encounters in hospitals reporting at least one culture with susceptibility testing for a given month to Premier Healthcare Database or Cerner Health Facts Database from 2012 to 2017. DTR was defined as intermediate susceptibility or resistance to all tested carbapenems, other β-lactams, and fluoroquinolones, but not including agents introduced 2014 onwards. For each year, a raking procedure generated weights to extrapolate the sample estimate to match American Hospital Association distributions based on US census division, hospital bed capacity, teaching status, and urban designation. A weighted means survey procedure was used to extrapolate the sample estimate to obtain national DTR burden. Trends in DTR incidence were examined by using weighted multivariable logistic regression. Results Extrapolating from a 373-hospital sample, the estimated 2017 US inpatient burden of DTR isolates was 3,315 (1.3%) among sterile-site and 31,509 (1.7%) among all cultures, ranging from 0.5% to 3.3% in Mountain and New England regions respectively. P. aeruginosa was the most common species overall (37%), while A. baumannii was most common among sterile sites (31%). Between 2012 and 2017, there was no annual percent change in DTR incidence for sterile sites [OR 0.99 (0.93, 1.06)] but for all cultures it decreased 4.1% annually [OR 0.95 (0.91, 0.99)], including 9% annually for A. baumannii [OR 0.905 (0.860, 0.953)] and K. pneumonia [OR 0.903 (0.824, 0.991)], respectively. Conclusion The US inpatient burden of GN isolates displaying DTR is relatively low, varies by region, and has remained stable or declined slightly in recent years. Periodic inclusion of emerging antibiotics in the DTR classification will allow for a dynamic index between resistance and available agents. Disclosures All Authors: No reported Disclosures.

Confidence interval for quantiles and percentiles

Quantiles and percentiles represent useful statistical tools for describing the distribution of results and deriving reference intervals and performance specification in laboratory medicine. They are commonly intended as the sample estimate of a population parameter and therefore they need to be presented with a confidence interval (CI). In this work we discuss three methods to estimate CI on quantiles and percentiles using parametric, nonparametric and resampling (bootstrap) approaches. The result of our numerical simulations is that parametric methods are always more accurate regardless of sample size when the procedure is appropriate for the distribution of results for both extreme (2.5th and 97.5th) and central (25th, 50th and 75th) percentiles and corresponding quantiles. We also show that both nonparametric and bootstrap methods suit well the CI of central percentiles that are used to derive performance specifications through quality indicators of laboratory processes whose underlying distribution is unknown.