Dependent Variable Sample Clauses
A Dependent Variable clause defines a specific factor or element within a contract or agreement whose value is determined by changes in another, independent variable. In practice, this clause identifies which outcomes, payments, or obligations will fluctuate based on external metrics, such as market rates, performance benchmarks, or other measurable criteria. By clearly establishing the relationship between variables, the clause ensures transparency and predictability in how contractual terms adjust, thereby reducing disputes and aligning expectations between parties.
Dependent Variable. Access to public officials of the European Commission
Dependent Variable. Perpetrated neglect Dependent variable: Perpetrated abuse Dependent variable: Perpetrated neglect
Dependent Variable. The Center for Epidemiologic Studies for depression (CES-D) scale was used to measure depressive symptoms. CES-D measures depressive symptoms on a scale of 0 to 60. It categorizes depressive symptoms as absent (<16 CES-D), mild (16-21), moderate (21-25) and severe (26-60) (▇▇▇▇▇▇▇ et al., 2016). We used greater than 16 to define depressive symptoms. There are 20 items in total, the participants’ answer for each item ranged from 0 to
Dependent Variable. Perpetrated neglect
Dependent Variable. ⮚ Improving the English language´s teaching-learning process.
Dependent Variable. Indicators of Obesity
Dependent Variable. The starting point of my dependent variable measurement is the definition of contagion that I have assumed. To recap, Kodres and ▇▇▇▇▇▇▇▇ (2002, 772) define 13 See Appendix III for the distribution of daily data by country and SDDS subscription status; see Appendix IV for descriptive information on each nation in the sample, including SDDS subscription details, geographical region and market type. contagion as “a general price movement in one market resulting from a shock in another market.” Given the authors’ specification of price movement, my measurement of contagion must be based on the value of a financial instrument. I have chosen government bonds as the study’s financial stability indicator since bond returns are determined by investors’ perception of investment risk. Government bonds have been issued and their returns quoted for a significant amount of time, so bond data is readily available. Furthermore, bonds are essential to government operations and are issued and traded regularly. Accordingly, the bond market is highly liquid and bond returns are generally accurate, especially in emerging economies where trading volumes are high. Alternative measures of country risk that were considered were stock market indices and credit default swap (CDS) rates. These instruments would be legitimate measures of volatility, but this paper only uses bond data to keep the scope tractable. The metric I have chosen to measure sovereign bond returns is ▇▇ ▇▇▇▇▇▇’▇ Emerging Market Bond Index (EMBI). The index is a bond return index, so lower values denote increased risk. The EMBI’s “[w]ell-defined liquidity criteria ensure the index provides a fair and replicable benchmark,” so there is no need to control for market illiquidity or trading volumes (▇▇ ▇▇▇▇▇▇). Finally, the EMBI has been widely employed in past research on contagion (▇▇▇▇▇▇▇▇ and Schmukler 2002; Alexander, et al. 2008; Glennester and Shin 2003; ▇▇▇▇▇▇▇▇, et al. 2003). A restriction of using the EMBI is that my sample is limited to a group of emerging markets that issue bonds and are quoted by the EMBI. However, these emerging markets are of the most interest in my theory and exhibit cross-country, cross-time variation on SDDS membership. To arrive at the final analysis of my contagion variable there were a series of intermediate steps. First, I transformed the EMBI index into daily percent change values. Then I conducted a regression of these daily changes with a variety of explanatory variable. The...
Dependent Variable. Table 1 shows the results testing H1: Juvenile offenders who have (a) weak conventional bonds to society and (b) low self-control are more likely to be susceptible than those with strong conventional bonds to society and high self-control. Table 1 has an adjusted R2 of .09 and is statistically significant at the .000 level. Overall, the results suggest that there are several significant factors that influence susceptibility, which include parental monitoring, perceptions of chances for success, grades, self-control, gender, and ethnicity. The social bonds variable, parental monitoring, is significant holding all other variables constant. However, the relationship is in the opposite direction that is hypothesized, which suggests that juveniles with strong parental monitoring are more likely to be susceptible. I will discuss this more below. Perceptions of chances for success is also highly statistically significant. This suggests that adolescents who have a better outlook on the future are less susceptible to peer influence. In the model, grades is modestly statistically significant, holding all other variables constant. This suggests that adolescents who report better grades are less susceptible to peer influence. The other social bond variables, bonding to teachers and maternal warmth, are not significant predictors of susceptibility. The second part of the first hypothesis is also tested in this model. Self-control has a relatively strong effect when regressed onto susceptibility, holding all other constant, and the relationship is in the hypothesized direction. This suggests that juveniles with greater self-control are less susceptible to their peers. Finally, the results indicate that ethnicity, namely African American, is significant at the .01 level. The direction of the relationship suggests that African Americans are less likely to be susceptible than their white counterparts. Also, sex is statistically significant, but only at the .05 level. This suggests that males are more susceptible than their female counterparts in the sample.
Dependent Variable. The Self-Report of Offending scale (Huizinga, Esbensen, & ▇▇▇▇▇▇ 1991) was adapted in this dataset to measure the respondents’ reports of antisocial and illegal activities. Twenty-four items are used to assess aggressive crimes, income- generating crimes, and public order offenses. These offenses include vandalism, arson, set fire, burglary, shoplifting, received stolen property, used credit card illegally, stole car, sold marijuana, sold other drugs, carjacked, drove drunk, been paid by someone for sex, forced someone to have sex, killed someone, shot someone, shot at someone, robbery with weapon, robbery with no weapon, beaten someone, in fight, fight part of gang, and carried gun. An offending variety score was created, which represents the number of different delinquent acts committed in the previous 6 months2 -- coded from 0 (no delinquent acts) to 1.0 (all 22 acts were committed). Variety scores have been previously used to assess criminal activity. For example, Hindelang, Hirschi, and Weis (1981) use variety scores to index criminal activity and other studies have been published on the validity of variety scores (▇▇▇▇▇▇▇▇ & ▇▇▇▇▇▇▇ 1985, 1986; ▇▇▇▇▇▇▇, ▇▇▇▇▇▇▇▇▇, & ▇▇▇▇▇▇▇ 2002). The variety score is used because it has the least skewed distribution of the self-report measures included in the dataset (see Appendix C).
Dependent Variable. Real-time App Usage Data Management