Recently, many humanoid robots have been increasingly deployed in various facilities, including hospitals and assisted living environments, where they are often remotely controlled by human operators. Their kinematic redundancy enhances reachability and manipulability, enabling them to navigate complex, cluttered environments and perform a wide range of tasks. However, this redundancy also presents significant control challenges, particularly in coordinating the movements of the robot's macro-micro structure (torso and arms). Therefore, we propose various human-robot collaborative (HRC) methods for coordinating the torso and arm of remotely controlled mobile humanoid robots, aiming to balance autonomy and human input to enhance system efficiency and task execution. The proposed methods include human-initiated approaches, where users manually control torso movements, and robot-initiated approaches, which autonomously coordinate torso and arm based on factors such as reachability, task goal, or inferred human intent. We conducted a user study with N=17 participants to compare the proposed approaches in terms of task performance, manipulability, and energy efficiency, and analyzed which methods were preferred by participants.